Analysis of the gut microbiome during pregnancy in T1D Metagenomics (NovaSeq)
Alexandra Roth Schulze
2020-02-26
1 Background
This report shows the analysis performed for metagenomics sequencing from the gut microbiome of 32 pregnant women. For each pregnant woman, samples were taken at 3 different time points during the pregnancy (i.e. corresponding to trimesters, up until day ~280 when the child is born) to give a total of 96 samples. From the 32 pregnant women, 16 are diabetic (T1D). For some analyses, time points were categorised into trimesters, correspondence being:
Trimester 1 = 0-99 days Trimester 2 = 100-196 days Trimester 3 = 196-280 days
2 Data generation
Samples were shotgun sequenced using the NovaSeq 6000 illumina sequencing machine at the Ramaciotti Centre for Genomics located at the University of New South Wales (UNSW) in Sydney, Australia.
2.1 Processing the sequences: from sequence data to feature table
The data was processed through pipelines developed by the group of Curtis Huttenhower at Harvard Univerisity and Broad Institute. These pipelines belong to the BioBakery.
The raw data was uploaded to the short read archive (SRA) database (https://www.ncbi.nlm.nih.gov/sra/) with accession number PRJNA604850.
- KneadData (https://bitbucket.org/biobakery/biobakery/wiki/kneaddata) was used to filter human (“contaminant”) sequences as well as quality controlling the sequences This has to be done for each sample. Example:
- kneaddata –input 4_S1_R1_001.fastq.gz –input 4_S1_R2_001.fastq.gz -db /home/users/allstaff/schulze.a/bin/Kneaddata/Homo_sapiens –trimmomatic /usr/local/bioinfsoftware/trimmomatic/trimmomatic-0.36 –output ./kneaddata_output -t 12
- HUMAnN2 (https://bitbucket.org/biobakery/humann2/wiki/Home) was employed to quantify gene families and pathways; and within HUMANn2, Metaphlan was also used to obtain taxonomic profiles. This process is also performed per sample and read pair1 and read pair2 need to be concatenated and saved in the same file prior to running HUMAn2 (i.e. end-pairing relationships are currently not taken into account during HUMAnN2’s alignment steps. This is due to the fact that HUMAnN2 strictly aligns reads to isolated coding sequences: either at the nucleotide level or through translated search. As such, it will frequently be the case that one read (READ1) will map inside a given coding sequence while its mate-pair (READ2) will not [information obtained from the manual]). Example of running HUMAnN2 with a sample:
- humann2 -i NGU5366A1.fastq -o ./Output_HUMAnN2 –threads 28
- Running this outputs several files, among those is “NGU5366A1_metaphlan_bugs_list.tsv”, which is a list of the bacterial taxa found in that sample at all taxonomic levels (i.e. stratified data) and their relative normalizaed abundances. The script merge_metaphlan_tables.py was used to merge the MetaPhlAn output from several samples into one table taxa (rows) vs samples (columns) with the table enlisting the relative normalized abundances per sample per taxa. Example:
- merge_metaphlan_tables.py metaphlan_output1.txt metaphlan_output2.txt metaphlan_output3.txt > ./merged_abundance_table_Rel_Abundance.txt
- As mentioned above, the abundance table (profile) contains the stratified data. In order to obtain a table that contains the taxa at a specific taxonomic level (e.g. Species), grep was used. Example for species taxonomic level:
- grep ’s__’ merged_abundance_table_Rel_Abundance.txt | grep -v ’t’ > merged_abundance_table_Rel_Abundance_Sp.tsv # -v (exclude) ’t’ will prevent from selecting those lines that have species and strain (’t__’) classification. We just need species in this case.
Example for genus taxonomic level:
- grep ’g__’ merged_abundance_table_Rel_Abundance.txt | grep -v ’t’ | grep -v ’s’ > merged_abundance_table_Rel_Abundance_Genus.tsv
Note: For other taxonomic levels, this process was repeated for each taxonomic level.
- This table contains the whole taxonomy for each taxa, from “kindom” to “Species” along with per sample abundances. Taxa classified as virus were removed. From this table the taxonomy (“Species_taxonomy.txt”) and the taxa (species) table (“merged_abundance_table_Rel_Abundance_Sp.tsv”) files were constructed. The taxa table is then transformed into a biom file in JSON format and the taxonomic and metadata infomation were added with the software biom. Example:
- biom convert -i merged_abundance_table_Rel_Abundance_Sp.tsv -o merged_abundance_table_Rel_Abundance_Sp.biom –table-type=“OTU table” –to-json
- biom add-metadata –sc-separated taxonomy –observation-header OTUID,taxonomy –observation-metadata-fp Species_taxonomy.txt -i merged_abundance_table_Rel_Abundance_Sp.biom -o Pregnancy_NovaSeq_taxonomic_profile_Rel_Species_NV_wTax.biom
- biom add-metadata -i Pregnancy_NovaSeq_taxonomic_profile_Rel_Species_NV_wTax.biom -o Pregnancy_NovaSeq_taxonomic_profile_Rel_Species_NV_wTaxMet.biom –sample-metadata-fp ./metadata.csv
This process was repeated at for each taxonomic level.
The resulting taxa tables (one for each taxonomic level) with taxonomies and metadata were imported into R to process with the Phyloseq (https://github.com/joey711/phyloseq) and other packages. The data were first de-identified (i.e. data relating to the identification of the donor was removed) and R object were saved. Those R objects were used as inputs in the analysis performed in this document.
3 Bar plots taxonomy
4 Alpha diversity
4.1 Alpha diversity (T1D vs. non-T1D continuous time [Days])
Call:
geeglm(formula = Observed ~ t1dfactor * days_c + age_c + nullip +
bmi_c + HLA, data = DivCal_R_df, id = motherid, corstr = "exchangeable")
Coefficients:
Estimate Std.err Wald Pr(>|W|)
(Intercept) 102.56782 2.40649 1816.586 < 2e-16 ***
t1dfactorT1D -0.12034 2.16713 0.003 0.95572
days_c 0.01784 0.02019 0.781 0.37689
age_c -0.22778 0.34311 0.441 0.50678
nullipYes -3.17432 2.54254 1.559 0.21185
bmi_c -0.44837 0.27895 2.584 0.10798
HLADRXX -9.12498 2.95011 9.567 0.00198 **
HLAGroup3o4 -4.98593 2.80853 3.152 0.07585 .
t1dfactorT1D:days_c -0.04773 0.03375 2.000 0.15731
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Estimated Scale Parameters:
Estimate Std.err
(Intercept) 104.2 12.54
Correlation: Structure = exchangeable Link = identity
Estimated Correlation Parameters:
Estimate Std.err
alpha 0.1932 0.127
Number of clusters: 83 Maximum cluster size: 3 4.2 Alpha diversity (T1D vs. non-T1D categorical time [Trimester])
Call:
geeglm(formula = Observed ~ t1dfactor * Tri + age_c + nullip +
bmi_c + HLA, data = DivCal_R_df, id = motherid, corstr = "exchangeable")
Coefficients:
Estimate Std.err Wald Pr(>|W|)
(Intercept) 103.100 3.355 944.63 <2e-16 ***
t1dfactorT1D 2.795 4.164 0.45 0.5020
TriT2 -1.873 2.928 0.41 0.5224
TriT3 2.587 3.555 0.53 0.4668
age_c -0.236 0.342 0.48 0.4892
nullipYes -2.984 2.572 1.35 0.2459
bmi_c -0.451 0.276 2.68 0.1017
HLADRXX -9.841 3.043 10.46 0.0012 **
HLAGroup3o4 -5.701 2.964 3.70 0.0545 .
t1dfactorT1D:TriT2 -1.973 5.090 0.15 0.6982
t1dfactorT1D:TriT3 -6.788 5.714 1.41 0.2349
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Estimated Scale Parameters:
Estimate Std.err
(Intercept) 104 12.4
Correlation: Structure = exchangeable Link = identity
Estimated Correlation Parameters:
Estimate Std.err
alpha 0.26 0.137
Number of clusters: 83 Maximum cluster size: 3 
5 Species taxonomic level
5.1 Microbial community composition analysis at Species level (Beta diversity analysi)
Hypothesis
Hypothesis: the gut microbiome taxonomic composition (i.e. Beta diversity) during pregnancy differs between women with and without T1D. In order to test if this hypothesis holds true, a measurement of the distance between each pair of samples is calculated (i.e. Bray-Curtis) and a repeated measure aware permutational analysis of variance (i.e. RMA-PERMANOVA) test is applied. A P-value <0.05 is considered to be significant, meaning that our hypothesis cannot be rejected. Borderline P-values are also considered positive.
Problems with the available R function for Beta diversity analysis
The current available function for performing hypothesis testing of differences in the microbiome composition between groups of samples is called Adonis (i.e. which perform a PERMANOVA test) and is part of the Rpackage vegan (Oksanen, J. et al). The main problem with this function is that if the metadata of interest does not vary with time (e.g. disease status, sex, etc.), adonis does not calculate the corresponding P value correctly, as it permutes levels within a subject. This does not make sense for something like disease status or sex as permuting within-subject will produce the exact same distribution each time you permute. This a known drawback of the adonis function for repeated measures.
In order to get the correct P-value for a time-invariant metadata, the permutation procedure has to be altered such that it permutes the subjects rather than levels within subjects, which apply to our current pregnancy dataset.
Here I’m running a script written by Jason Lloyd-Price from Curtis Huttenhower lab in Harvard. This script is being used instead of the regular Adonis (PERMANOVA test) from the R package Vegan because as stated above, our metadata of interest (i.e. T1D status) does not vary with time, we have a mixture of data which changes within and between an individual and we also have unequal group sizes (i.e. we do not always have exactly 3 samples per woman). For those three reasons, it was recommended to use his script to perform the RMA-PERMANOVA analysis.
PARAMETERS:
permute_within: This data frame has samples on rows and metadata on columns. This should only contain metadata that varies within a block (i.e. it’s a single-column data frame with only time/Days).Since, the other metadata within the block should be the same between repeated measurements and this will not hold when we introduce other factor i.e. sequencing run, BMI, parity, gestational age (i.e. Days or trimester) and conception age , those five factors should be placed here
blocks: This should just be a vector giving the group of each sample (i.e. the motherid vector; motherid is strictly accounting for personID but not for pregnancy per se).
block_data: This data frame contains per-block metadata, with one row per block (motherid). It should only contain metadata pertaining to the blocks (i.e. T1Dstatus). motherid is not numeric, ensure that the row names match the factor names in the motherid vector (blocks).
metadata_order: This is needed if you want to specify a particular order that the model should be fit in. Metadata earlier in the list will be fit and residualized first, so these should be features we are NOT interested in and want to control for.
Results from PERMANOVA test with repeat measure-aware permutations - Controlling for Days/Trimester, sequencing run, conception age, BMI, parity and HLA type
Here the blocking factor is taking into account each mother who might have given samples from different trimesters or two different pregnancies (i.e. motherid is the name of the factor). Therefore, the factor “motherid” takes into account two different pregnancies from the same mother as one SubjectID to adjust for repeated measurements
The interaction between T1D status and time was also included in order to test if the differences between T1D and non-T1D women in the same or changes throguhout pregnancy.
5.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 1.59 0.529 2.93 0.076 0.002 **
Days 1 0.13 0.130 0.72 0.006 0.177
T1D_Time_Interaction 1 0.70 0.702 3.89 0.034 0.001 ***
Age 1 0.61 0.609 3.37 0.029 0.980
Parity 1 0.60 0.601 3.33 0.029 0.231
BMI 1 0.55 0.546 3.02 0.026 0.882
HLA 2 1.36 0.682 3.77 0.065 0.080 .
T1Dstatus 1 0.23 0.229 1.27 0.011 0.993
Residuals 84 15.18 0.181 0.725 0.319
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.001Due to the interaction between T1D and time having a significant P-value, differences in beta diversity between T1D and non-T1D was assessed by trimester using a normal PERMANOVA with the adonis function.
5.1.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.57 0.191 0.800 0.111 0.88
Nulliparous 1 0.34 0.337 1.414 0.065 0.11
Age_LMP 1 0.24 0.238 1.001 0.046 0.47
BMI_conception 1 0.26 0.263 1.104 0.051 0.35
HLA.6DRML 2 0.36 0.178 0.747 0.069 0.89
T1Dstatus 1 0.28 0.283 1.187 0.055 0.25
Residuals 13 3.10 0.238 0.602
Total 22 5.14 1.000 [1] 0.253Beta diversity Plot
5.1.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.71 0.237 1.12 0.103 0.229
Nulliparous 1 0.25 0.251 1.19 0.036 0.225
Age_LMP 1 0.25 0.253 1.20 0.037 0.235
BMI_conception 1 0.24 0.241 1.14 0.035 0.291
HLA.6DRML 2 0.51 0.255 1.21 0.074 0.150
T1Dstatus 1 0.31 0.312 1.48 0.045 0.067 .
Residuals 22 4.65 0.211 0.671
Total 31 6.92 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.067Beta diversity Plot
5.1.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.71 0.237 1.16 0.103 0.187
Nulliparous 1 0.21 0.210 1.02 0.030 0.428
Age_LMP 1 0.29 0.291 1.42 0.042 0.081 .
BMI_conception 1 0.28 0.279 1.36 0.040 0.088 .
HLA.6DRML 2 0.47 0.234 1.14 0.068 0.228
T1Dstatus 1 0.44 0.442 2.16 0.064 0.001 ***
Residuals 22 4.50 0.205 0.652
Total 31 6.90 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.001Beta diversity Plot
5.1.5 Days within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.14 0.572 4.05 0.112 0.265
seqRun 3 1.74 0.580 4.11 0.171 0.319
Age 1 0.56 0.564 3.99 0.055 0.857
Parity 1 0.67 0.666 4.71 0.065 0.033 *
BMI 1 0.58 0.575 4.07 0.056 0.755
Days 1 0.13 0.133 0.94 0.013 0.068 .
Residuals 38 5.37 0.141 0.527 0.163
Total 47 10.19 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
5.1.6 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.14 0.572 4.01 0.112 0.263
seqRun 3 1.74 0.580 4.07 0.171 0.291
Age 1 0.56 0.564 3.95 0.055 0.855
Parity 1 0.67 0.666 4.66 0.065 0.036 *
BMI 1 0.58 0.575 4.03 0.056 0.737
Tri 2 0.22 0.110 0.77 0.022 0.183
Residuals 37 5.28 0.143 0.518 0.150
Total 47 10.19 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
5.1.7 Days within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.35 0.675 5.00 0.135 0.122
seqRun 3 1.55 0.517 3.82 0.155 0.816
Age 1 1.17 1.168 8.65 0.117 0.009 **
Parity 1 0.37 0.375 2.78 0.037 0.983
BMI 1 0.30 0.297 2.20 0.030 0.823
Days 1 0.16 0.155 1.15 0.015 0.035 *
Residuals 38 5.13 0.135 0.512 0.040 *
Total 47 10.03 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
5.1.8 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.35 0.675 4.88 0.135 0.114
seqRun 3 1.55 0.517 3.74 0.155 0.838
Age 1 1.17 1.168 8.45 0.117 0.006 **
Parity 1 0.37 0.375 2.71 0.037 0.989
BMI 1 0.30 0.297 2.15 0.030 0.835
Tri 2 0.17 0.087 0.63 0.017 0.602
Residuals 37 5.11 0.138 0.510 0.100 .
Total 47 10.03 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
5.1.9 Other factors
5.1.9.1 Age at conception
5.1.9.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.38 0.059 0.225
T1Dstatus 1 0.85 0.848 4.66 0.040 0.037 *
seqRun 3 1.66 0.554 3.05 0.079 0.203
Tri 2 0.24 0.121 0.67 0.012 0.465
Age 1 0.61 0.610 3.35 0.029 0.306
Parity 1 0.54 0.544 2.99 0.026 0.826
BMI 1 0.57 0.566 3.11 0.027 0.578
Age_Time_Interaction 1 0.14 0.144 0.79 0.007 0.105
Residuals 83 15.10 0.182 0.721 0.036 *
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.37 0.059 0.255
T1Dstatus 1 0.85 0.848 4.64 0.040 0.038 *
seqRun 3 1.66 0.554 3.03 0.079 0.190
Tri 2 0.24 0.121 0.66 0.012 0.465
Age 1 0.61 0.610 3.34 0.029 0.290
Parity 1 0.54 0.544 2.98 0.026 0.827
BMI 1 0.57 0.566 3.10 0.027 0.588
Age_Time_Interaction 1 0.08 0.082 0.45 0.004 0.684
Residuals 83 15.16 0.183 0.724 0.050 *
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.37 0.059 0.218
T1Dstatus 1 0.85 0.848 4.65 0.040 0.026 *
seqRun 3 1.66 0.554 3.04 0.079 0.201
Tri 2 0.24 0.121 0.66 0.012 0.497
Age 1 0.61 0.610 3.34 0.029 0.287
Parity 1 0.54 0.544 2.98 0.026 0.817
BMI 1 0.57 0.566 3.10 0.027 0.615
Age_Time_Interaction 1 0.10 0.099 0.54 0.005 0.256
Residuals 83 15.15 0.182 0.723 0.037 *
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.1.4 Age at conception (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.39 0.059 0.221
T1Dstatus 1 0.85 0.848 4.67 0.040 0.028 *
seqRun 3 1.66 0.554 3.05 0.079 0.215
Tri 2 0.24 0.121 0.67 0.012 0.456
Parity 1 0.53 0.534 2.94 0.026 0.831
BMI 1 0.59 0.592 3.26 0.028 0.423
Age 1 0.59 0.593 3.27 0.028 0.503
Residuals 84 15.25 0.181 0.728 0.045 *
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.2 Body max index (BMI)
5.1.9.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.37 0.059 0.214
T1Dstatus 1 0.85 0.848 4.64 0.040 0.038 *
seqRun 3 1.66 0.554 3.03 0.079 0.205
Tri 2 0.24 0.121 0.66 0.012 0.484
Age 1 0.61 0.610 3.34 0.029 0.291
Parity 1 0.54 0.544 2.98 0.026 0.832
BMI 1 0.57 0.566 3.10 0.027 0.596
BMI_Time_Interaction 1 0.09 0.092 0.50 0.004 0.684
Residuals 83 15.15 0.183 0.723 0.059 .
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.36 0.059 0.219
T1Dstatus 1 0.85 0.848 4.63 0.040 0.026 *
seqRun 3 1.66 0.554 3.03 0.079 0.199
Tri 2 0.24 0.121 0.66 0.012 0.508
Age 1 0.61 0.610 3.33 0.029 0.316
Parity 1 0.54 0.544 2.97 0.026 0.826
BMI 1 0.57 0.566 3.09 0.027 0.566
BMI_Time_Interaction 1 0.05 0.050 0.27 0.002 0.982
Residuals 83 15.20 0.183 0.725 0.056 .
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.2.3 BMI interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.37 0.059 0.230
T1Dstatus 1 0.85 0.848 4.64 0.040 0.025 *
seqRun 3 1.66 0.554 3.03 0.079 0.203
Tri 2 0.24 0.121 0.66 0.012 0.458
Age 1 0.61 0.610 3.34 0.029 0.308
Parity 1 0.54 0.544 2.98 0.026 0.816
BMI 1 0.57 0.566 3.10 0.027 0.573
BMI_Time_Interaction 1 0.09 0.091 0.50 0.004 0.113
Residuals 83 15.15 0.183 0.723 0.033 *
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.2.4 BMI (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.39 0.059 0.217
T1Dstatus 1 0.85 0.848 4.67 0.040 0.038 *
seqRun 3 1.66 0.554 3.05 0.079 0.200
Tri 2 0.24 0.121 0.67 0.012 0.473
Age 1 0.61 0.610 3.36 0.029 0.316
Parity 1 0.54 0.544 3.00 0.026 0.835
BMI 1 0.57 0.566 3.12 0.027 0.583
Residuals 84 15.25 0.181 0.728 0.033 *
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.3 HLA type
5.1.9.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.39 0.059 0.231
T1Dstatus 1 0.85 0.848 4.66 0.040 0.044 *
Days 1 0.13 0.131 0.72 0.006 0.220
seqRun 3 1.66 0.552 3.04 0.079 0.189
Age 1 0.60 0.601 3.30 0.029 0.371
Parity 1 0.55 0.545 3.00 0.026 0.828
BMI 1 0.56 0.561 3.09 0.027 0.618
HLA_Time_Interaction 1 0.10 0.104 0.57 0.005 1.000
Residuals 84 15.27 0.182 0.729 0.594
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.39 0.059 0.24
T1Dstatus 1 0.85 0.848 4.66 0.040 0.04 *
Days 1 0.13 0.131 0.72 0.006 0.19
seqRun 3 1.66 0.552 3.04 0.079 0.19
Age 1 0.60 0.601 3.30 0.029 0.41
Parity 1 0.55 0.545 3.00 0.026 0.81
BMI 1 0.56 0.561 3.09 0.027 0.60
HLA_Time_Interaction 1 0.10 0.099 0.55 0.005 1.00
Residuals 84 15.28 0.182 0.729 0.32
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.39 0.059 0.223
T1Dstatus 1 0.85 0.848 4.67 0.040 0.028 *
Days 1 0.13 0.131 0.72 0.006 0.195
seqRun 3 1.66 0.552 3.04 0.079 0.222
Age 1 0.60 0.601 3.31 0.029 0.369
Parity 1 0.55 0.545 3.00 0.026 0.818
BMI 1 0.56 0.561 3.09 0.027 0.614
HLA_Time_Interaction 1 0.13 0.129 0.71 0.006 1.000
Residuals 84 15.25 0.182 0.728 0.277
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.14 0.139 0.77 0.007 0.149
seqRun 3 1.58 0.526 2.91 0.075 0.631
Age 1 0.59 0.585 3.23 0.028 0.958
Parity 1 0.61 0.607 3.35 0.029 0.146
BMI 1 0.58 0.580 3.21 0.028 0.731
T1Dstatus 1 0.69 0.688 3.80 0.033 0.168
HLA 2 1.40 0.699 3.86 0.067 0.082 .
Residuals 85 15.38 0.181 0.734 0.043 *
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.4 Parity
5.1.9.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.39 0.059 0.233
T1Dstatus 1 0.85 0.848 4.67 0.040 0.044 *
Days 1 0.13 0.131 0.72 0.006 0.197
seqRun 3 1.66 0.552 3.04 0.079 0.224
Age 1 0.60 0.601 3.31 0.029 0.365
Parity 1 0.55 0.545 3.00 0.026 0.828
BMI 1 0.56 0.561 3.09 0.027 0.621
Parity_Time_Interaction 1 0.12 0.116 0.64 0.006 0.155
Residuals 84 15.26 0.182 0.728 0.038 *
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.4.2 Parity (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.40 0.059 0.254
T1Dstatus 1 0.85 0.848 4.69 0.040 0.044 *
Days 1 0.13 0.131 0.72 0.006 0.213
seqRun 3 1.66 0.552 3.05 0.079 0.193
BMI 1 0.72 0.717 3.97 0.034 0.452
Age 1 0.59 0.589 3.26 0.028 0.501
Parity 1 0.40 0.401 2.22 0.019 0.878
Residuals 85 15.38 0.181 0.734 0.042 *
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.5 Mode of delivery
5.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.57 0.059 0.259
T1Dstatus 1 0.85 0.848 4.92 0.040 0.026 *
MOD 2 1.08 0.539 3.12 0.051 0.469
Days 1 0.13 0.130 0.76 0.006 0.194
seqRun 3 1.58 0.527 3.06 0.075 0.484
Age 1 0.68 0.681 3.95 0.032 0.076 .
Parity 1 0.53 0.527 3.06 0.025 0.808
BMI 1 0.62 0.617 3.58 0.029 0.341
MOD_Time_Interaction 1 0.12 0.117 0.68 0.006 1.000
Residuals 82 14.14 0.172 0.675 0.435
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.56 0.059 0.200
T1Dstatus 1 0.85 0.848 4.90 0.040 0.031 *
MOD 2 1.08 0.539 3.11 0.051 0.487
Days 1 0.13 0.130 0.75 0.006 0.193
seqRun 3 1.58 0.527 3.05 0.075 0.477
Age 1 0.68 0.681 3.93 0.032 0.088 .
Parity 1 0.53 0.527 3.05 0.025 0.789
BMI 1 0.62 0.617 3.56 0.029 0.363
MOD_Time_Interaction 1 0.07 0.069 0.40 0.003 1.000
Residuals 82 14.19 0.173 0.677 0.212
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.56 0.059 0.222
T1Dstatus 1 0.85 0.848 4.90 0.040 0.035 *
MOD 2 1.08 0.539 3.12 0.051 0.460
Days 1 0.13 0.130 0.75 0.006 0.162
seqRun 3 1.58 0.527 3.05 0.075 0.492
Age 1 0.68 0.681 3.94 0.032 0.081 .
Parity 1 0.53 0.527 3.05 0.025 0.793
BMI 1 0.62 0.617 3.57 0.029 0.339
MOD_Time_Interaction 1 0.08 0.081 0.47 0.004 1.000
Residuals 82 14.17 0.173 0.677 0.328
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.14 0.139 0.81 0.007 0.168
seqRun 3 1.58 0.526 3.06 0.075 0.665
Age 1 0.59 0.585 3.41 0.028 0.948
Parity 1 0.61 0.607 3.53 0.029 0.152
BMI 1 0.58 0.580 3.38 0.028 0.739
HLA 2 1.21 0.603 3.51 0.058 0.257
T1Dstatus 1 0.88 0.880 5.12 0.042 0.024 *
MOD 2 1.12 0.560 3.26 0.053 0.402
Residuals 83 14.26 0.172 0.681 0.065 .
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.6 Carbohydrate intake
5.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.43 0.059 0.223
T1Dstatus 1 0.85 0.848 4.72 0.040 0.035 *
Carbs 1 0.45 0.455 2.53 0.022 0.722
seqRun 3 1.65 0.550 3.06 0.079 0.249
Tri 2 0.24 0.118 0.66 0.011 0.458
Age 1 0.55 0.553 3.08 0.026 0.702
Parity 1 0.54 0.538 3.00 0.026 0.775
BMI 1 0.60 0.605 3.37 0.029 0.380
Carb_Time_Interaction 1 0.10 0.104 0.58 0.005 0.966
Residuals 82 14.73 0.180 0.703 0.155
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.41 0.059 0.246
T1Dstatus 1 0.85 0.848 4.70 0.040 0.048 *
Carbs 1 0.45 0.455 2.52 0.022 0.684
seqRun 3 1.65 0.550 3.05 0.079 0.257
Tri 2 0.24 0.118 0.66 0.011 0.457
Age 1 0.55 0.553 3.07 0.026 0.695
Parity 1 0.54 0.538 2.99 0.026 0.797
BMI 1 0.60 0.605 3.35 0.029 0.402
Carb_Time_Interaction 1 0.04 0.043 0.24 0.002 1.000
Residuals 82 14.79 0.180 0.706 0.260
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.42 0.059 0.271
T1Dstatus 1 0.85 0.848 4.71 0.040 0.035 *
Carbs 1 0.45 0.455 2.53 0.022 0.723
seqRun 3 1.65 0.550 3.06 0.079 0.274
Tri 2 0.24 0.118 0.66 0.011 0.477
Age 1 0.55 0.553 3.07 0.026 0.688
Parity 1 0.54 0.538 2.99 0.026 0.818
BMI 1 0.60 0.605 3.36 0.029 0.389
Carb_Time_Interaction 1 0.07 0.070 0.39 0.003 0.995
Residuals 82 14.76 0.180 0.705 0.186
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.6.4 Carbohydrate (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 1.59 0.529 2.96 0.076 0.001 ***
Tri 2 0.26 0.130 0.73 0.012 0.475
Age 1 0.59 0.594 3.33 0.028 0.622
Parity 1 0.61 0.609 3.41 0.029 0.200
BMI 1 0.58 0.578 3.23 0.028 0.845
HLA 2 1.19 0.594 3.33 0.057 0.241
T1Dstatus 1 0.89 0.888 4.97 0.042 0.022 *
Carbs 1 0.41 0.414 2.31 0.020 0.795
Residuals 83 14.83 0.179 0.708 0.098 .
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.7 Fibre intake
5.1.9.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.40 0.059 0.222
T1Dstatus 1 0.85 0.848 4.69 0.040 0.034 *
Fiber 1 0.35 0.352 1.95 0.017 0.940
seqRun 3 1.62 0.541 2.99 0.077 0.345
Tri 2 0.24 0.122 0.67 0.012 0.413
Age 1 0.57 0.574 3.18 0.027 0.589
Parity 1 0.54 0.544 3.00 0.026 0.757
BMI 1 0.60 0.603 3.33 0.029 0.415
Fiber_Time_Interaction 1 0.10 0.097 0.53 0.005 0.929
Residuals 82 14.83 0.181 0.708 0.198
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.39 0.059 0.249
T1Dstatus 1 0.85 0.848 4.67 0.040 0.037 *
Fiber 1 0.35 0.352 1.94 0.017 0.937
seqRun 3 1.62 0.541 2.98 0.077 0.348
Tri 2 0.24 0.122 0.67 0.012 0.460
Age 1 0.57 0.574 3.16 0.027 0.569
Parity 1 0.54 0.544 2.99 0.026 0.773
BMI 1 0.60 0.603 3.32 0.029 0.402
Fiber_Time_Interaction 1 0.04 0.043 0.24 0.002 1.000
Residuals 82 14.89 0.182 0.711 0.332
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.23 0.616 3.40 0.059 0.230
T1Dstatus 1 0.85 0.848 4.68 0.040 0.023 *
Fiber 1 0.35 0.352 1.94 0.017 0.925
seqRun 3 1.62 0.541 2.98 0.077 0.323
Tri 2 0.24 0.122 0.67 0.012 0.451
Age 1 0.57 0.574 3.17 0.027 0.534
Parity 1 0.54 0.544 3.00 0.026 0.764
BMI 1 0.60 0.603 3.33 0.029 0.411
Fiber_Time_Interaction 1 0.07 0.073 0.40 0.003 0.992
Residuals 82 14.86 0.181 0.709 0.239
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.7.4 Fibre (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 1.59 0.529 2.94 0.076 0.001 ***
Tri 2 0.26 0.130 0.72 0.012 0.450
Age 1 0.59 0.594 3.30 0.028 0.643
Parity 1 0.61 0.609 3.38 0.029 0.203
BMI 1 0.58 0.578 3.21 0.028 0.813
HLA 2 1.19 0.594 3.30 0.057 0.259
T1Dstatus 1 0.89 0.888 4.93 0.042 0.026 *
Fiber 1 0.31 0.314 1.75 0.015 0.954
Residuals 83 14.93 0.180 0.713 0.201
Total 95 20.95 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.8 1,5-AG (glucose control measurement)
5.1.9.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.33 0.664 3.86 0.067 0.120
T1Dstatus 1 0.87 0.868 5.05 0.044 0.029 *
Days 1 0.12 0.125 0.73 0.006 0.387
seqRun 3 1.62 0.539 3.13 0.081 0.306
Age 1 0.63 0.630 3.66 0.032 0.225
Parity 1 0.55 0.550 3.20 0.028 0.767
BMI 1 0.50 0.499 2.90 0.025 0.750
AG15 1 0.59 0.592 3.44 0.030 0.017 *
AG15_T1D_Interaction 1 0.38 0.379 2.20 0.019 0.887
Residuals 77 13.25 0.172 0.668 0.018 *
Total 89 19.83 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.16 0.581 4.33 0.128 0.197
Days 1 0.24 0.239 1.78 0.026 0.020 *
seqRun 3 1.56 0.521 3.89 0.173 0.778
Age 1 0.45 0.454 3.38 0.050 0.930
Parity 1 0.69 0.694 5.17 0.077 0.016 *
BMI 1 0.56 0.555 4.14 0.061 0.708
AG15 1 0.23 0.230 1.71 0.025 0.948
Residuals 31 4.16 0.134 0.459 0.438
Total 41 9.05 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.35 0.675 5.34 0.135 0.129
Days 1 0.15 0.153 1.21 0.015 0.033 *
seqRun 3 1.56 0.519 4.11 0.155 0.791
Age 1 1.16 1.164 9.22 0.116 0.008 **
Parity 1 0.38 0.380 3.01 0.038 0.979
BMI 1 0.29 0.290 2.29 0.029 0.856
AG15 1 0.46 0.457 3.62 0.046 0.858
Residuals 37 4.67 0.126 0.466 0.104
Total 47 10.03 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.2 Differential abundance analysis Species taxonomic level
Differential abundance analysis with limma using voom pipeline with structural zeros - Gordon
Improved analysis using TMM normalization and voom with structural zeros.
A linear model is fit to the data and differential abundance is assessed using empirical bayes. The false discovery rate (FDR) for this analysis is set at 5%. For a OTU to be classified as differentially abundant (DA), its change in abundance between the groups (T1D vs nonT1D) must be significant. In the results tables to follow, the genes that are DE are those that have an adjusted p-value less than the FDR. Note that adjusted p-value is used opposed to the initial p-value as it has been adjusted for multiple testing. Therefore any adjusted p-value less than 0.05 is deemed statistically significant, identifying the associated gene as DA.
Those genes that are DA are then determined to be more- or less abundant depending on the direction of their log-fold change. Those OTUs with a positive log-fold change are more abundant, while those OTUs with a negative log-fold change are less abundant.
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 9 2 1 9 0 0 0 0 0 0
NotSig 288 295 297 288 298 298 298 298 298 298
Up 1 1 0 1 0 0 0 0 0 0
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 0 0
NotSig 298 298 298
Up 0 0 0Differentially abundant species were found between T1D and non-T1D women across pregnancy and within each trimester. No differentially abundant species were detected between trimesters in samples form T1D and non-T1D women together or separatelly.
Results for contrasts with significant differentially abundant species are shown below
5.2.1 Across all trimesters (T1D vs non-T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean%
5 Bacteroides_uniformis -1.373 4.11e-03 0.08745 5.240 100.0 7.768
8 Escherichia_coli -1.046 1.18e-05 0.00176 0.109 87.5 0.869
2 Bacteroides_eggerthii -1.025 6.71e-04 0.03333 0.680 100.0 4.296
6 Alistipes_sp_AP11 -1.007 1.52e-04 0.00904 0.331 41.7 1.551
1 Bacteroides_clarus -0.898 4.87e-05 0.00484 0.011 37.5 0.545
7 Roseburia_hominis -0.784 3.28e-03 0.07975 0.338 93.8 0.775
9 Escherichia_unclassified -0.711 1.01e-03 0.04171 0.027 77.1 0.278
3 Bacteroides_intestinalis -0.660 3.48e-03 0.07975 0.600 62.5 0.228
4 Bacteroides_massiliensis 0.945 1.44e-03 0.04281 2.659 100.0 1.575
T1D:Prev%
5 100.0
8 89.6
2 100.0
6 50.0
1 60.4
7 93.8
9 79.2
3 60.4
4 100.0First part of the code used to plot Figure 3 of the article. This and other coded parts in the differential abundance analysis have the specific figures and ordering (i.e. as specified by the letters (Let variable)) of the composed figure used for the manuscript. Note that, as per described in the article, only taxa with prevalence > 50% in either group in the comparison, are considered.
5.2.2 Only Trimester 1 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean%
5 Escherichia_coli -1.362 3.06e-05 0.00912 0.065 72.7 1.374
4 Alistipes_sp_AP11 -1.194 8.40e-04 0.06256 0.145 36.4 1.234
3 Bacteroides_salyersiae -1.044 1.27e-03 0.07302 0.182 18.2 0.611
1 Bacteroides_clarus -0.956 1.47e-03 0.07302 0.029 36.4 0.832
2 Bacteroides_massiliensis 1.535 1.05e-04 0.01557 2.031 100.0 0.282
T1D:Prev%
5 83.3
4 50.0
3 50.0
1 66.7
2 100.0[1] 145.2.3 Only Trimester 2 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Bacteroides_salyersiae -1.04 0.000134 0.0399 0.087 25.0
2 Bacteroides_salyersiae -1.04 0.000134 0.0399 0.945 37.5After filtering low prevalent taxa, no species was significantly different between T1D and non-T1D women in this comparison.
5.2.4 Only Trimester 3 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean%
8 Bacteroides_uniformis -2.071 2.90e-04 0.01150 3.033 100.0 8.692
4 Bacteroides_eggerthii -1.339 1.63e-04 0.01150 0.300 100.0 4.166
2 Bacteroides_caccae -1.323 2.84e-04 0.01150 0.639 100.0 1.905
7 Bacteroides_salyersiae -1.316 3.79e-06 0.00113 0.178 43.8 1.084
10 Roseburia_hominis -1.282 5.65e-05 0.00715 0.244 100.0 0.837
9 Parabacteroides_distasonis -1.206 2.81e-04 0.01150 0.283 100.0 2.068
12 Sutterella_wadsworthensis -1.085 3.89e-03 0.08287 1.050 93.8 1.520
13 Escherichia_coli -1.024 3.09e-04 0.01150 0.163 93.8 0.760
3 Bacteroides_clarus -0.912 5.76e-04 0.01907 0.009 31.2 0.303
6 Bacteroides_intestinalis -0.796 3.17e-03 0.07882 0.238 81.2 0.254
5 Bacteroides_faecis -0.779 4.41e-03 0.08760 0.134 93.8 0.948
14 Escherichia_unclassified -0.750 3.82e-03 0.08287 0.032 81.2 0.232
11 Ruminococcus_bromii 0.976 4.96e-03 0.09241 1.855 93.8 0.305
1 Bifidobacterium_adolescentis 1.056 8.21e-04 0.02447 2.325 81.2 0.083
T1D:Prev%
8 100.0
4 100.0
2 100.0
7 50.0
10 93.8
9 100.0
12 100.0
13 100.0
3 50.0
6 81.2
5 81.2
14 68.8
11 100.0
1 81.25.2.5 T1 vs T2 (All data)
[1] "No DA taxa found"Nothing left after filtering by prevalence and LogFC
5.2.6 T2 vs T3 (All data)
[1] "No DA taxa"Nothing left after filtering by prevalence and LogFC
5.2.7 T1 vs T3 (All data)
[1] "No DA taxa found"5.2.8 T1 vs T2 (in women with T1D)
[1] "No DA taxa found"5.2.9 T2 vs T3 (in women with T1D)
[1] "No DA taxa found"5.2.10 T1 vs T3 (in women with T1D)
[1] "No DA taxa found"5.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa found"5.2.12 T2 vs T3 (in women without T1D)
[1] "No DA taxa found"5.2.13 T1 vs T3 (in women without T1D)
[1] "No DA taxa found"6 Strain taxonomic level
6.1 Microbial community composition analysis at strain level (Beta diversity analysis)
6.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 1.52 0.506 2.64 0.069 0.174
Days 1 0.15 0.150 0.78 0.007 0.102
T1D_Time_Interaction 1 0.80 0.800 4.18 0.036 0.006 **
Age 1 0.64 0.637 3.33 0.029 0.986
Parity 1 0.61 0.607 3.17 0.027 0.118
BMI 1 0.56 0.556 2.90 0.025 0.797
HLA 2 1.51 0.753 3.93 0.068 0.044 *
T1Dstatus 1 0.26 0.265 1.38 0.012 0.989
Residuals 84 16.10 0.192 0.727 0.236
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.0066.1.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.56 0.187 0.723 0.102 0.95
Nulliparous 1 0.33 0.334 1.289 0.060 0.18
Age_LMP 1 0.25 0.253 0.978 0.046 0.49
BMI_conception 1 0.29 0.285 1.101 0.052 0.36
HLA.6DRML 2 0.40 0.200 0.774 0.072 0.84
T1Dstatus 1 0.33 0.327 1.265 0.059 0.20
Residuals 13 3.37 0.259 0.609
Total 22 5.53 1.000 [1] 0.195Beta diversity Plot
6.1.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.71 0.236 1.07 0.097 0.341
Nulliparous 1 0.25 0.250 1.13 0.034 0.289
Age_LMP 1 0.26 0.265 1.20 0.036 0.213
BMI_conception 1 0.25 0.250 1.13 0.034 0.308
HLA.6DRML 2 0.59 0.295 1.33 0.081 0.079 .
T1Dstatus 1 0.36 0.362 1.64 0.050 0.020 *
Residuals 22 4.88 0.222 0.668
Total 31 7.30 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.02Beta diversity Plot
6.1.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.71 0.235 1.07 0.096 0.308
Nulliparous 1 0.23 0.231 1.04 0.031 0.400
Age_LMP 1 0.28 0.283 1.28 0.039 0.128
BMI_conception 1 0.29 0.288 1.30 0.039 0.115
HLA.6DRML 2 0.52 0.261 1.18 0.071 0.163
T1Dstatus 1 0.45 0.452 2.05 0.062 0.002 **
Residuals 22 4.85 0.221 0.662
Total 31 7.34 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.002Beta diversity Plot
6.1.5 Days within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.25 0.624 4.24 0.118 0.162
seqRun 3 1.66 0.552 3.76 0.157 0.604
Age 1 0.47 0.475 3.23 0.045 0.859
Parity 1 0.77 0.766 5.21 0.073 0.032 *
BMI 1 0.67 0.665 4.53 0.063 0.769
Days 1 0.15 0.146 0.99 0.014 0.029 *
Residuals 38 5.58 0.147 0.530 0.100 .
Total 47 10.54 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
6.1.6 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.25 0.624 4.20 0.118 0.17
seqRun 3 1.66 0.552 3.72 0.157 0.60
Age 1 0.47 0.475 3.20 0.045 0.87
Parity 1 0.77 0.766 5.16 0.073 0.03 *
BMI 1 0.67 0.665 4.48 0.063 0.78
Tri 2 0.24 0.118 0.79 0.022 0.10
Residuals 37 5.49 0.149 0.521 0.13
Total 47 10.54 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
6.1.7 Days within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.725 4.84 0.136 0.111
seqRun 3 1.45 0.483 3.22 0.135 0.916
Age 1 1.21 1.209 8.06 0.113 0.005 **
Parity 1 0.37 0.365 2.43 0.034 0.991
BMI 1 0.34 0.342 2.28 0.032 0.691
Days 1 0.18 0.184 1.23 0.017 0.013 *
Residuals 38 5.70 0.150 0.533 0.064 .
Total 47 10.70 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
6.1.8 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.725 4.73 0.136 0.126
seqRun 3 1.45 0.483 3.15 0.135 0.923
Age 1 1.21 1.209 7.89 0.113 0.011 *
Parity 1 0.37 0.365 2.38 0.034 0.986
BMI 1 0.34 0.342 2.23 0.032 0.656
Tri 2 0.21 0.106 0.69 0.020 0.417
Residuals 37 5.67 0.153 0.530 0.153
Total 47 10.70 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
6.1.9 Other factors
6.1.9.1 Age at conception
6.1.9.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.76 0.066 0.098 .
T1Dstatus 1 1.00 0.997 5.16 0.045 0.015 *
seqRun 3 1.49 0.498 2.57 0.067 0.599
Tri 2 0.25 0.126 0.65 0.011 0.466
Age 1 0.64 0.641 3.31 0.029 0.344
Parity 1 0.54 0.537 2.78 0.024 0.842
BMI 1 0.58 0.579 2.99 0.026 0.616
Age_Time_Interaction 1 0.14 0.143 0.74 0.006 0.132
Residuals 83 16.04 0.193 0.725 0.025 *
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.75 0.066 0.120
T1Dstatus 1 1.00 0.997 5.14 0.045 0.015 *
seqRun 3 1.49 0.498 2.56 0.067 0.608
Tri 2 0.25 0.126 0.65 0.011 0.444
Age 1 0.64 0.641 3.30 0.029 0.336
Parity 1 0.54 0.537 2.77 0.024 0.855
BMI 1 0.58 0.579 2.98 0.026 0.621
Age_Time_Interaction 1 0.08 0.082 0.42 0.004 0.713
Residuals 83 16.10 0.194 0.727 0.028 *
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.75 0.066 0.094 .
T1Dstatus 1 1.00 0.997 5.15 0.045 0.011 *
seqRun 3 1.49 0.498 2.57 0.067 0.627
Tri 2 0.25 0.126 0.65 0.011 0.453
Age 1 0.64 0.641 3.31 0.029 0.351
Parity 1 0.54 0.537 2.77 0.024 0.843
BMI 1 0.58 0.579 2.99 0.026 0.648
Age_Time_Interaction 1 0.10 0.104 0.54 0.005 0.225
Residuals 83 16.08 0.194 0.726 0.019 *
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.1.4 Age at conception (no interaction and within trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.57 0.286 1.106 0.104 0.20
T1Dstatus 1 0.26 0.260 1.006 0.047 0.40
seqRun 3 0.50 0.168 0.650 0.091 0.95
Parity 1 0.32 0.321 1.242 0.058 0.53
BMI 1 0.32 0.324 1.253 0.059 0.20
Age 1 0.18 0.178 0.688 0.032 0.93
Residuals 13 3.37 0.259 0.609 0.64
Total 22 5.53 1.000 6.1.9.1.5 Age at conception (no interaction and within trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.76 0.382 1.97 0.087 0.110
T1Dstatus 1 0.55 0.552 2.84 0.063 0.005 **
seqRun 3 0.84 0.279 1.44 0.095 0.927
Parity 1 0.29 0.291 1.50 0.033 0.709
BMI 1 0.23 0.232 1.20 0.026 0.662
Age 1 0.31 0.307 1.58 0.035 0.286
Residuals 30 5.83 0.194 0.661 0.027 *
Total 39 8.81 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.1.6 Age at conception (no interaction and within trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.57 0.287 1.313 0.076 0.253
T1Dstatus 1 0.44 0.436 1.997 0.058 0.007 **
seqRun 3 0.74 0.247 1.132 0.098 0.297
Parity 1 0.21 0.211 0.968 0.028 0.895
BMI 1 0.28 0.282 1.294 0.037 0.787
Age 1 0.28 0.275 1.261 0.036 0.415
Residuals 23 5.02 0.218 0.666 0.045 *
Total 32 7.54 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.2 Body max index (BMI)
6.1.9.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.75 0.066 0.117
T1Dstatus 1 1.00 0.997 5.15 0.045 0.009 **
seqRun 3 1.49 0.498 2.57 0.067 0.614
Tri 2 0.25 0.126 0.65 0.011 0.489
Age 1 0.64 0.641 3.31 0.029 0.360
Parity 1 0.54 0.537 2.77 0.024 0.844
BMI 1 0.58 0.579 2.99 0.026 0.631
BMI_Time_Interaction 1 0.10 0.101 0.52 0.005 0.608
Residuals 83 16.08 0.194 0.727 0.031 *
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.74 0.066 0.077 .
T1Dstatus 1 1.00 0.997 5.13 0.045 0.017 *
seqRun 3 1.49 0.498 2.56 0.067 0.641
Tri 2 0.25 0.126 0.65 0.011 0.476
Age 1 0.64 0.641 3.30 0.029 0.351
Parity 1 0.54 0.537 2.77 0.024 0.810
BMI 1 0.58 0.579 2.98 0.026 0.626
BMI_Time_Interaction 1 0.06 0.062 0.32 0.003 0.930
Residuals 83 16.12 0.194 0.728 0.024 *
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.2.3 BMI interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.75 0.066 0.093 .
T1Dstatus 1 1.00 0.997 5.15 0.045 0.013 *
seqRun 3 1.49 0.498 2.57 0.067 0.615
Tri 2 0.25 0.126 0.65 0.011 0.473
Age 1 0.64 0.641 3.31 0.029 0.336
Parity 1 0.54 0.537 2.77 0.024 0.826
BMI 1 0.58 0.579 2.99 0.026 0.599
BMI_Time_Interaction 1 0.10 0.104 0.54 0.005 0.054 .
Residuals 83 16.08 0.194 0.726 0.018 *
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.2.4 BMI (no interaction but within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.57 0.286 1.155 0.104 0.23
T1Dstatus 1 0.26 0.260 1.051 0.047 0.41
seqRun 1 0.22 0.215 0.869 0.039 0.73
Age 1 0.23 0.233 0.939 0.042 0.89
Parity 1 0.29 0.286 1.153 0.052 0.72
BMI 1 0.24 0.243 0.981 0.044 0.67
Residuals 15 3.72 0.248 0.673 0.59
Total 22 5.53 1.000 6.1.9.2.5 BMI (no interaction but within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.76 0.382 1.92 0.087 0.095 .
T1Dstatus 1 0.55 0.552 2.77 0.063 0.008 **
seqRun 1 0.32 0.321 1.61 0.036 0.939
Age 1 0.29 0.294 1.48 0.033 0.285
Parity 1 0.29 0.293 1.47 0.033 0.713
BMI 1 0.22 0.217 1.09 0.025 0.536
Residuals 32 6.37 0.199 0.723 0.014 *
Total 39 8.81 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.2.6 BMI (no interaction but within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.57 0.287 1.29 0.076 0.212
T1Dstatus 1 0.44 0.436 1.97 0.058 0.010 **
seqRun 1 0.24 0.243 1.09 0.032 0.065 .
Age 1 0.29 0.292 1.32 0.039 0.366
Parity 1 0.21 0.206 0.93 0.027 0.914
BMI 1 0.24 0.245 1.10 0.032 0.810
Residuals 25 5.54 0.222 0.735 0.031 *
Total 32 7.54 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.3 HLA type
6.1.9.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.77 0.066 0.096 .
T1Dstatus 1 1.00 0.997 5.18 0.045 0.014 *
Days 1 0.15 0.148 0.77 0.007 0.127
seqRun 3 1.49 0.496 2.57 0.067 0.611
Age 1 0.63 0.629 3.26 0.028 0.412
Parity 1 0.54 0.544 2.82 0.025 0.836
BMI 1 0.57 0.569 2.95 0.026 0.659
HLA_Time_Interaction 1 0.12 0.123 0.64 0.006 1.000
Residuals 84 16.18 0.193 0.731 0.466
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.77 0.066 0.094 .
T1Dstatus 1 1.00 0.997 5.18 0.045 0.010 **
Days 1 0.15 0.148 0.77 0.007 0.146
seqRun 3 1.49 0.496 2.57 0.067 0.629
Age 1 0.63 0.629 3.26 0.028 0.413
Parity 1 0.54 0.544 2.82 0.025 0.827
BMI 1 0.57 0.569 2.95 0.026 0.649
HLA_Time_Interaction 1 0.12 0.119 0.61 0.005 1.000
Residuals 84 16.19 0.193 0.731 0.180
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.77 0.066 0.083 .
T1Dstatus 1 1.00 0.997 5.18 0.045 0.014 *
Days 1 0.15 0.148 0.77 0.007 0.131
seqRun 3 1.49 0.496 2.58 0.067 0.649
Age 1 0.63 0.629 3.27 0.028 0.412
Parity 1 0.54 0.544 2.82 0.025 0.821
BMI 1 0.57 0.569 2.96 0.026 0.689
HLA_Time_Interaction 1 0.14 0.135 0.70 0.006 1.000
Residuals 84 16.17 0.193 0.731 0.200
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.16 0.158 0.82 0.007 0.115
seqRun 3 1.51 0.503 2.62 0.068 0.528
Age 1 0.61 0.613 3.20 0.028 0.950
Parity 1 0.61 0.608 3.17 0.027 0.054 .
BMI 1 0.59 0.592 3.08 0.027 0.778
T1Dstatus 1 0.80 0.798 4.16 0.036 0.100 .
HLA 2 1.55 0.775 4.04 0.070 0.051 .
Residuals 85 16.31 0.192 0.737 0.016 *
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.4 Parity
6.1.9.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.78 0.066 0.078 .
T1Dstatus 1 1.00 0.997 5.18 0.045 0.019 *
Days 1 0.15 0.148 0.77 0.007 0.134
seqRun 3 1.49 0.496 2.58 0.067 0.644
Age 1 0.63 0.629 3.27 0.028 0.408
Parity 1 0.54 0.544 2.83 0.025 0.835
BMI 1 0.57 0.569 2.96 0.026 0.672
Parity_Time_Interaction 1 0.14 0.143 0.74 0.006 0.050 *
Residuals 84 16.16 0.192 0.730 0.014 *
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.4.2 Parity (no interaction but within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.57 0.286 1.155 0.104 0.21
T1Dstatus 1 0.26 0.260 1.051 0.047 0.40
seqRun 1 0.22 0.215 0.869 0.039 0.75
Age 1 0.23 0.233 0.939 0.042 0.86
BMI 1 0.25 0.254 1.026 0.046 0.85
Parity 1 0.27 0.275 1.107 0.050 0.45
Residuals 15 3.72 0.248 0.673 0.58
Total 22 5.53 1.000 6.1.9.4.3 Parity (no interaction but within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.76 0.382 1.92 0.087 0.092 .
T1Dstatus 1 0.55 0.552 2.77 0.063 0.005 **
seqRun 1 0.32 0.321 1.61 0.036 0.915
Age 1 0.29 0.294 1.48 0.033 0.315
BMI 1 0.30 0.303 1.52 0.034 0.451
Parity 1 0.21 0.208 1.04 0.024 0.812
Residuals 32 6.37 0.199 0.723 0.014 *
Total 39 8.81 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.4.4 Parity (no interaction but within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.57 0.287 1.29 0.076 0.219
T1Dstatus 1 0.44 0.436 1.97 0.058 0.010 **
seqRun 1 0.24 0.243 1.09 0.032 0.061 .
Age 1 0.29 0.292 1.32 0.039 0.355
BMI 1 0.23 0.227 1.02 0.030 0.661
Parity 1 0.22 0.224 1.01 0.030 0.918
Residuals 25 5.54 0.222 0.735 0.026 *
Total 32 7.54 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.5 Mode of delivery
6.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 4.01 0.066 0.099 .
T1Dstatus 1 1.00 0.997 5.51 0.045 0.022 *
MOD 2 1.11 0.555 3.06 0.050 0.573
Days 1 0.15 0.148 0.82 0.007 0.117
seqRun 3 1.54 0.512 2.83 0.069 0.471
Age 1 0.76 0.762 4.21 0.034 0.059 .
Parity 1 0.51 0.515 2.84 0.023 0.840
BMI 1 0.62 0.622 3.43 0.028 0.406
MOD_Time_Interaction 1 0.15 0.145 0.80 0.007 1.000
Residuals 82 14.85 0.181 0.671 0.184
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 4.00 0.066 0.106
T1Dstatus 1 1.00 0.997 5.49 0.045 0.012 *
MOD 2 1.11 0.555 3.05 0.050 0.537
Days 1 0.15 0.148 0.82 0.007 0.100 .
seqRun 3 1.54 0.512 2.82 0.069 0.457
Age 1 0.76 0.762 4.19 0.034 0.056 .
Parity 1 0.51 0.515 2.83 0.023 0.840
BMI 1 0.62 0.622 3.42 0.028 0.388
MOD_Time_Interaction 1 0.08 0.085 0.47 0.004 1.000
Residuals 82 14.91 0.182 0.673 0.092 .
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 4.00 0.066 0.092 .
T1Dstatus 1 1.00 0.997 5.49 0.045 0.009 **
MOD 2 1.11 0.555 3.05 0.050 0.559
Days 1 0.15 0.148 0.82 0.007 0.116
seqRun 3 1.54 0.512 2.82 0.069 0.470
Age 1 0.76 0.762 4.19 0.034 0.051 .
Parity 1 0.51 0.515 2.83 0.023 0.864
BMI 1 0.62 0.622 3.42 0.028 0.364
MOD_Time_Interaction 1 0.10 0.100 0.55 0.005 1.000
Residuals 82 14.89 0.182 0.673 0.149
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.16 0.158 0.87 0.007 0.100 .
seqRun 3 1.51 0.503 2.79 0.068 0.572
Age 1 0.61 0.613 3.39 0.028 0.958
Parity 1 0.61 0.608 3.37 0.027 0.058 .
BMI 1 0.59 0.592 3.28 0.027 0.806
HLA 2 1.38 0.690 3.82 0.062 0.171
T1Dstatus 1 0.97 0.968 5.36 0.044 0.025 *
MOD 2 1.31 0.657 3.64 0.059 0.209
Residuals 83 14.99 0.181 0.677 0.009 **
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.6 Carbohydrate intake
6.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.80 0.066 0.092 .
T1Dstatus 1 1.00 0.997 5.21 0.045 0.014 *
Carbs 1 0.45 0.453 2.36 0.020 0.782
seqRun 3 1.49 0.496 2.59 0.067 0.638
Tri 2 0.25 0.123 0.64 0.011 0.500
Age 1 0.59 0.588 3.07 0.027 0.661
Parity 1 0.51 0.514 2.68 0.023 0.889
BMI 1 0.59 0.587 3.07 0.027 0.542
Carb_Time_Interaction 1 0.11 0.114 0.60 0.005 0.949
Residuals 82 15.70 0.191 0.709 0.144
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.78 0.066 0.11
T1Dstatus 1 1.00 0.997 5.19 0.045 0.01 **
Carbs 1 0.45 0.453 2.35 0.020 0.79
seqRun 3 1.49 0.496 2.58 0.067 0.65
Tri 2 0.25 0.123 0.64 0.011 0.51
Age 1 0.59 0.588 3.06 0.027 0.62
Parity 1 0.51 0.514 2.67 0.023 0.88
BMI 1 0.59 0.587 3.05 0.027 0.54
Carb_Time_Interaction 1 0.04 0.042 0.22 0.002 1.00
Residuals 82 15.77 0.192 0.712 0.22
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.79 0.066 0.10
T1Dstatus 1 1.00 0.997 5.20 0.045 0.01 **
Carbs 1 0.45 0.453 2.36 0.020 0.80
seqRun 3 1.49 0.496 2.59 0.067 0.66
Tri 2 0.25 0.123 0.64 0.011 0.48
Age 1 0.59 0.588 3.07 0.027 0.65
Parity 1 0.51 0.514 2.68 0.023 0.87
BMI 1 0.59 0.587 3.06 0.027 0.55
Carb_Time_Interaction 1 0.08 0.085 0.44 0.004 0.99
Residuals 82 15.73 0.192 0.710 0.13
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.6.4 Carbohydrate (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 1.52 0.506 2.66 0.069 0.147
Tri 2 0.27 0.134 0.70 0.012 0.477
Age 1 0.63 0.625 3.28 0.028 0.574
Parity 1 0.61 0.607 3.18 0.027 0.155
BMI 1 0.59 0.595 3.12 0.027 0.777
HLA 2 1.36 0.682 3.58 0.062 0.161
T1Dstatus 1 0.98 0.976 5.12 0.044 0.018 *
Carbs 1 0.37 0.374 1.96 0.017 0.919
Residuals 83 15.81 0.190 0.714 0.105
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.7 Fibre intake
6.1.9.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.79 0.066 0.083 .
T1Dstatus 1 1.00 0.997 5.20 0.045 0.019 *
Fiber 1 0.39 0.389 2.03 0.018 0.908
seqRun 3 1.47 0.490 2.55 0.066 0.725
Tri 2 0.25 0.126 0.66 0.011 0.432
Age 1 0.60 0.600 3.13 0.027 0.552
Parity 1 0.52 0.523 2.73 0.024 0.844
BMI 1 0.60 0.600 3.13 0.027 0.479
Fiber_Time_Interaction 1 0.11 0.111 0.58 0.005 0.888
Residuals 82 15.74 0.192 0.711 0.145
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.77 0.066 0.087 .
T1Dstatus 1 1.00 0.997 5.17 0.045 0.012 *
Fiber 1 0.39 0.389 2.02 0.018 0.930
seqRun 3 1.47 0.490 2.54 0.066 0.707
Tri 2 0.25 0.126 0.66 0.011 0.403
Age 1 0.60 0.600 3.11 0.027 0.599
Parity 1 0.52 0.523 2.71 0.024 0.845
BMI 1 0.60 0.600 3.11 0.027 0.477
Fiber_Time_Interaction 1 0.04 0.043 0.22 0.002 1.000
Residuals 82 15.81 0.193 0.714 0.227
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.727 3.78 0.066 0.105
T1Dstatus 1 1.00 0.997 5.19 0.045 0.015 *
Fiber 1 0.39 0.389 2.03 0.018 0.913
seqRun 3 1.47 0.490 2.55 0.066 0.697
Tri 2 0.25 0.126 0.66 0.011 0.441
Age 1 0.60 0.600 3.12 0.027 0.565
Parity 1 0.52 0.523 2.72 0.024 0.849
BMI 1 0.60 0.600 3.12 0.027 0.488
Fiber_Time_Interaction 1 0.09 0.089 0.46 0.004 0.959
Residuals 82 15.76 0.192 0.712 0.142
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.7.4 Fibre (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 1.52 0.506 2.65 0.069 0.152
Tri 2 0.27 0.134 0.70 0.012 0.468
Age 1 0.63 0.625 3.27 0.028 0.558
Parity 1 0.61 0.607 3.18 0.027 0.151
BMI 1 0.59 0.595 3.11 0.027 0.786
HLA 2 1.36 0.682 3.57 0.062 0.182
T1Dstatus 1 0.98 0.976 5.11 0.044 0.022 *
Fiber 1 0.33 0.334 1.75 0.015 0.961
Residuals 83 15.85 0.191 0.716 0.126
Total 95 22.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.8 1,5-AG (glucose control measurement)
6.1.9.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.54 0.771 4.18 0.073 0.066 .
T1Dstatus 1 1.01 1.013 5.49 0.048 0.013 *
Days 1 0.14 0.143 0.78 0.007 0.314
seqRun 3 1.40 0.468 2.54 0.067 0.767
Age 1 0.67 0.674 3.66 0.032 0.259
Parity 1 0.56 0.556 3.01 0.026 0.779
BMI 1 0.51 0.512 2.77 0.024 0.743
AG15 1 0.59 0.595 3.22 0.028 0.020 *
AG15_T1D_Interaction 1 0.34 0.340 1.84 0.016 0.979
Residuals 77 14.21 0.184 0.677 0.011 *
Total 89 20.98 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.27 0.634 4.51 0.135 0.138
Days 1 0.23 0.233 1.66 0.025 0.020 *
seqRun 3 1.45 0.482 3.43 0.154 0.943
Age 1 0.39 0.387 2.75 0.041 0.936
Parity 1 0.79 0.790 5.62 0.084 0.018 *
BMI 1 0.64 0.639 4.54 0.068 0.677
AG15 1 0.24 0.241 1.72 0.026 0.963
Residuals 31 4.36 0.141 0.466 0.443
Total 41 9.37 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.45 0.725 5.14 0.136 0.115
Days 1 0.18 0.181 1.28 0.017 0.028 *
seqRun 3 1.45 0.483 3.42 0.136 0.942
Age 1 1.21 1.209 8.57 0.113 0.010 **
Parity 1 0.37 0.374 2.65 0.035 0.987
BMI 1 0.34 0.335 2.38 0.031 0.727
AG15 1 0.48 0.478 3.39 0.045 0.858
Residuals 37 5.22 0.141 0.488 0.153
Total 47 10.70 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.2 Differential abundance analysis Strain taxonomic level
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 0 0 0 0 0 0 0 0 0 0
NotSig 267 267 267 267 267 267 71 267 267 76
Up 0 0 0 0 0 0 196 0 0 191
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 0 0
NotSig 267 267 266
Up 0 0 16.2.1 Across all trimesters (T1D vs non-T1D)
[1] "No DA taxa found"6.2.2 Only Trimester 1 (nonT1D vs T1D)
[1] "No DA taxa found"6.2.3 Only Trimester 2 (nonT1D vs T1D)
[1] "No DA taxa found"6.2.4 Only Trimester 3 (nonT1D vs T1D)
[1] "No DA taxa found"6.2.5 T1 vs T2 (All data)
Classification LogFC P.Val adj.P.Val
1 Eubacterium_siraeum_St_Eubacterium_siraeum_unclassified 0.583 0.04450 0.0720
2 Ruminococcus_bromii_St_GCF_000209875 0.517 0.00724 0.0671
T1:mean% T1Prev% T2:mean% T2Prev% T3:mean% T3Prev%
1 5.78 100 4.31 100 2.51 100
2 1.52 100 1.63 100 1.05 976.2.6 T2 vs T3 (All data)
[1] "No DA taxa"6.2.7 T1 vs T3 (All data)
Classification LogFC P.Val
1 Eubacterium_siraeum_St_Eubacterium_siraeum_unclassified 0.816 5.52e-03
2 Ruminococcus_bromii_St_GCF_000209875 0.767 9.92e-05
3 Haemophilus_parainfluenzae_St_Haemophilus_parainfluenzae_unclassified 0.599 7.98e-06
adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev% T3:mean% T3Prev%
1 0.02084 5.776 100.0 4.306 100 2.513 100.0
2 0.00883 1.519 100.0 1.629 100 1.047 97.0
3 0.00213 0.201 78.3 0.111 75 0.052 48.5No differentially abundant strains were detected between T1D and non-T1D women accross trimesters or in each trimesters separatelly (i.e. nonT1D_vs_T1D, T1, T2 and T3 contrasts had no strains up or down). In addition no differences between T1 and T2 (i.e. contrast T1_vs_T2) and between T2 and T3 (contrast T2_vs_T3) were found when samples from T1D and non-T1D women were assessed together. In T1D women only and in non-T1D women only, significant differences were detected only between trimesters 1 and 3 (i.e. T1DT1vsT3 and noT1DT1vsT3, respectively)
Results for contrasts with significant differentially abundant strains shown below
6.2.8 T1 vs T2 (in women with T1D)
Classification LogFC P.Val
2 Bacteroides_massiliensis_St_Bacteroides_massiliensis_unclassified -0.558 0.042732
3 Lachnospiraceae_bacterium_8_1_57FAA_St_GCF_000185545 0.509 0.001732
1 Collinsella_aerofaciens_St_GCF_000169035 0.522 0.019438
5 Akkermansia_muciniphila_St_GCF_000020225 0.708 0.042569
4 Ruminococcus_bromii_St_GCF_000209875 0.893 0.000859
adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
2 0.0872 0.282 100 1.852 100
3 0.0872 0.096 50 0.049 45
1 0.0872 0.998 75 0.799 85
5 0.0872 3.384 100 1.331 100
4 0.0817 1.647 100 0.867 100[1] 56.2.9 T2 vs T3 (in women with T1D)
[1] Classification LogFC P.Val adj.P.Val T2:mean%
[6] T2Prev% T3:mean% T3Prev%
<0 rows> (or 0-length row.names)6.2.10 T1 vs T3 (in women with T1D)
Classification LogFC
7 Oxalobacter_formigenes_St_Oxalobacter_formigenes_unclassified 0.537
4 Lachnospiraceae_bacterium_8_1_57FAA_St_GCF_000185545 0.579
2 Parabacteroides_goldsteinii_St_Parabacteroides_goldsteinii_unclassified 0.595
1 Bifidobacterium_adolescentis_St_Bifidobacterium_adolescentis_unclassified 0.612
5 Roseburia_intestinalis_St_Roseburia_intestinalis_unclassified 0.692
3 Eubacterium_siraeum_St_Eubacterium_siraeum_unclassified 0.713
8 Akkermansia_muciniphila_St_GCF_000020225 0.967
6 Ruminococcus_bromii_St_GCF_000209875 1.228
P.Val adj.P.Val T1:mean% T1Prev% T3:mean% T3Prev%
7 5.96e-04 0.03976 0.079 58.3 0.010 50.0
4 4.25e-04 0.03779 0.096 50.0 0.036 37.5
2 1.87e-03 0.04082 0.665 41.7 0.403 56.2
1 1.88e-02 0.04082 0.633 75.0 0.083 81.2
5 3.19e-03 0.04082 0.590 66.7 0.118 68.8
3 7.73e-02 0.09252 1.798 100.0 2.428 100.0
8 6.74e-03 0.04082 3.384 100.0 1.031 100.0
6 8.30e-06 0.00222 1.647 100.0 0.305 100.0[1] 136.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa found"6.2.12 T2 vs T3 (in women without T1D)
[1] "No DA taxa found"6.2.13 T1 vs T3 (in women without T1D)
Classification LogFC P.Val
1 Haemophilus_parainfluenzae_St_Haemophilus_parainfluenzae_unclassified 0.718 0.000169
2 Haemophilus_parainfluenzae_St_Haemophilus_parainfluenzae_unclassified 0.718 0.000169
adj.P.Val mean% Prev%
1 0.0452 0.189 90.9
2 0.0452 0.052 52.9[1] 147 Genus taxonomic level
7.1 Microbial community composition analysis at Genus level (Beta diversity analysis)
7.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.74 0.247 2.68 0.069 0.018 *
Days 1 0.11 0.109 1.18 0.010 0.090 .
T1D_Time_Interaction 1 0.51 0.513 5.55 0.048 0.006 **
Age 1 0.42 0.420 4.55 0.039 0.995
Parity 1 0.26 0.259 2.81 0.024 0.009 **
BMI 1 0.28 0.279 3.02 0.026 0.994
HLA 2 0.54 0.270 2.92 0.050 0.315
T1Dstatus 1 0.12 0.118 1.27 0.011 0.913
Residuals 84 7.76 0.092 0.723 0.353
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.0067.1.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.275 0.0918 0.756 0.102 0.81
Nulliparous 1 0.154 0.1537 1.265 0.057 0.26
Age_LMP 1 0.170 0.1705 1.403 0.063 0.17
BMI_conception 1 0.132 0.1322 1.089 0.049 0.38
HLA.6DRML 2 0.208 0.1041 0.857 0.077 0.62
T1Dstatus 1 0.179 0.1792 1.475 0.066 0.15
Residuals 13 1.579 0.1215 0.585
Total 22 2.698 1.000 [1] 0.152Beta diversity Plot
7.1.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.40 0.1325 1.18 0.109 0.27
Nulliparous 1 0.08 0.0841 0.75 0.023 0.64
Age_LMP 1 0.17 0.1666 1.49 0.046 0.16
BMI_conception 1 0.15 0.1462 1.30 0.040 0.22
HLA.6DRML 2 0.24 0.1191 1.06 0.065 0.37
T1Dstatus 1 0.14 0.1374 1.23 0.038 0.28
Residuals 22 2.47 0.1122 0.678
Total 31 3.64 1.000 [1] 0.279Beta diversity Plot
7.1.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.29 0.0970 0.932 0.082 0.560
Nulliparous 1 0.14 0.1427 1.370 0.040 0.180
Age_LMP 1 0.16 0.1557 1.495 0.044 0.137
BMI_conception 1 0.22 0.2192 2.105 0.062 0.047 *
HLA.6DRML 2 0.16 0.0809 0.777 0.046 0.730
T1Dstatus 1 0.29 0.2879 2.765 0.081 0.015 *
Residuals 22 2.29 0.1041 0.645
Total 31 3.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.015Beta diversity Plot
7.1.5 Days within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.32 0.160 2.52 0.069 0.698
seqRun 3 0.75 0.251 3.95 0.163 0.608
Age 1 0.37 0.375 5.90 0.081 0.354
Parity 1 0.36 0.363 5.73 0.079 0.014 *
BMI 1 0.27 0.272 4.28 0.059 0.820
Days 1 0.12 0.122 1.93 0.026 0.021 *
Residuals 38 2.41 0.063 0.523 0.190
Total 47 4.62 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
7.1.6 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.32 0.160 2.48 0.069 0.728
seqRun 3 0.75 0.251 3.89 0.163 0.551
Age 1 0.37 0.375 5.81 0.081 0.356
Parity 1 0.36 0.363 5.63 0.079 0.016 *
BMI 1 0.27 0.272 4.22 0.059 0.772
Tri 2 0.15 0.074 1.15 0.032 0.115
Residuals 37 2.39 0.065 0.517 0.241
Total 47 4.62 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
7.1.7 Days within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.68 0.342 4.15 0.121 0.241
seqRun 3 0.58 0.193 2.34 0.103 0.902
Age 1 0.78 0.783 9.50 0.139 0.066 .
Parity 1 0.13 0.129 1.57 0.023 0.970
BMI 1 0.21 0.210 2.55 0.037 0.474
Days 1 0.13 0.130 1.58 0.023 0.035 *
Residuals 38 3.13 0.082 0.554 0.186
Total 47 5.64 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
7.1.8 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.68 0.342 4.06 0.121 0.210
seqRun 3 0.58 0.193 2.29 0.103 0.915
Age 1 0.78 0.783 9.28 0.139 0.052 .
Parity 1 0.13 0.129 1.53 0.023 0.976
BMI 1 0.21 0.210 2.49 0.037 0.469
Tri 2 0.14 0.070 0.83 0.025 0.320
Residuals 37 3.12 0.084 0.553 0.234
Total 47 5.64 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
7.1.9 Other factors
7.1.9.1 Age at conception
7.1.9.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.46 0.044 0.616
T1Dstatus 1 0.56 0.564 5.95 0.053 0.025 *
seqRun 3 0.69 0.231 2.43 0.064 0.699
Tri 2 0.11 0.056 0.60 0.011 0.610
Age 1 0.43 0.426 4.49 0.040 0.275
Parity 1 0.24 0.237 2.50 0.022 0.736
BMI 1 0.31 0.308 3.25 0.029 0.739
Age_Time_Interaction 1 0.05 0.054 0.56 0.005 0.581
Residuals 83 7.87 0.095 0.733 0.255
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.45 0.044 0.602
T1Dstatus 1 0.56 0.564 5.92 0.053 0.031 *
seqRun 3 0.69 0.231 2.42 0.064 0.694
Tri 2 0.11 0.056 0.59 0.011 0.636
Age 1 0.43 0.426 4.47 0.040 0.297
Parity 1 0.24 0.237 2.49 0.022 0.702
BMI 1 0.31 0.308 3.23 0.029 0.715
Age_Time_Interaction 1 0.01 0.011 0.11 0.001 0.984
Residuals 83 7.92 0.095 0.737 0.320
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.46 0.044 0.594
T1Dstatus 1 0.56 0.564 5.94 0.053 0.026 *
seqRun 3 0.69 0.231 2.43 0.064 0.668
Tri 2 0.11 0.056 0.59 0.011 0.596
Age 1 0.43 0.426 4.49 0.040 0.315
Parity 1 0.24 0.237 2.50 0.022 0.713
BMI 1 0.31 0.308 3.24 0.029 0.750
Age_Time_Interaction 1 0.04 0.037 0.39 0.003 0.703
Residuals 83 7.89 0.095 0.735 0.250
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.1.4 Age at conception (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.48 0.044 0.574
T1Dstatus 1 0.56 0.564 5.98 0.053 0.029 *
seqRun 3 0.69 0.231 2.44 0.064 0.684
Tri 2 0.11 0.056 0.60 0.011 0.599
Parity 1 0.21 0.212 2.25 0.020 0.800
BMI 1 0.36 0.363 3.84 0.034 0.582
Age 1 0.40 0.397 4.21 0.037 0.434
Residuals 84 7.93 0.094 0.738 0.211
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.2 Body max index (BMI)
7.1.9.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.46 0.044 0.621
T1Dstatus 1 0.56 0.564 5.93 0.053 0.028 *
seqRun 3 0.69 0.231 2.43 0.064 0.672
Tri 2 0.11 0.056 0.59 0.011 0.635
Age 1 0.43 0.426 4.48 0.040 0.283
Parity 1 0.24 0.237 2.50 0.022 0.690
BMI 1 0.31 0.308 3.24 0.029 0.742
BMI_Time_Interaction 1 0.03 0.031 0.32 0.003 0.883
Residuals 83 7.90 0.095 0.736 0.268
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.45 0.044 0.573
T1Dstatus 1 0.56 0.564 5.92 0.053 0.027 *
seqRun 3 0.69 0.231 2.42 0.064 0.672
Tri 2 0.11 0.056 0.59 0.011 0.620
Age 1 0.43 0.426 4.48 0.040 0.317
Parity 1 0.24 0.237 2.49 0.022 0.721
BMI 1 0.31 0.308 3.24 0.029 0.746
BMI_Time_Interaction 1 0.02 0.020 0.21 0.002 0.917
Residuals 83 7.91 0.095 0.736 0.278
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.2.3 BMI interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.46 0.044 0.581
T1Dstatus 1 0.56 0.564 5.94 0.053 0.031 *
seqRun 3 0.69 0.231 2.43 0.064 0.677
Tri 2 0.11 0.056 0.59 0.011 0.617
Age 1 0.43 0.426 4.49 0.040 0.286
Parity 1 0.24 0.237 2.50 0.022 0.696
BMI 1 0.31 0.308 3.25 0.029 0.733
BMI_Time_Interaction 1 0.05 0.046 0.49 0.004 0.378
Residuals 83 7.88 0.095 0.734 0.215
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.2.4 BMI (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.48 0.044 0.589
T1Dstatus 1 0.56 0.564 5.98 0.053 0.025 *
seqRun 3 0.69 0.231 2.44 0.064 0.684
Tri 2 0.11 0.056 0.60 0.011 0.611
Age 1 0.43 0.426 4.52 0.040 0.264
Parity 1 0.24 0.237 2.52 0.022 0.704
BMI 1 0.31 0.308 3.27 0.029 0.745
Residuals 84 7.93 0.094 0.738 0.213
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.3 HLA type
7.1.9.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.48 0.044 0.609
T1Dstatus 1 0.56 0.564 6.00 0.053 0.030 *
Days 1 0.12 0.117 1.24 0.011 0.088 .
seqRun 3 0.68 0.227 2.42 0.064 0.703
Age 1 0.41 0.413 4.39 0.039 0.369
Parity 1 0.24 0.236 2.51 0.022 0.715
BMI 1 0.30 0.302 3.21 0.028 0.766
HLA_Time_Interaction 1 0.05 0.048 0.51 0.004 1.000
Residuals 84 7.91 0.094 0.736 0.564
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.49 0.044 0.587
T1Dstatus 1 0.56 0.564 6.01 0.053 0.023 *
Days 1 0.12 0.117 1.24 0.011 0.082 .
seqRun 3 0.68 0.227 2.42 0.064 0.717
Age 1 0.41 0.413 4.40 0.039 0.373
Parity 1 0.24 0.236 2.51 0.022 0.738
BMI 1 0.30 0.302 3.21 0.028 0.795
HLA_Time_Interaction 1 0.06 0.064 0.68 0.006 0.998
Residuals 84 7.89 0.094 0.735 0.324
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.49 0.044 0.579
T1Dstatus 1 0.56 0.564 6.01 0.053 0.035 *
Days 1 0.12 0.117 1.24 0.011 0.082 .
seqRun 3 0.68 0.227 2.42 0.064 0.702
Age 1 0.41 0.413 4.40 0.039 0.350
Parity 1 0.24 0.236 2.51 0.022 0.722
BMI 1 0.30 0.302 3.21 0.028 0.783
HLA_Time_Interaction 1 0.06 0.060 0.64 0.006 0.955
Residuals 84 7.89 0.094 0.735 0.226
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.12 0.121 1.30 0.011 0.102
seqRun 3 0.73 0.243 2.60 0.068 0.728
Age 1 0.39 0.391 4.18 0.036 0.994
Parity 1 0.27 0.271 2.90 0.025 0.003 **
BMI 1 0.35 0.354 3.79 0.033 0.897
T1Dstatus 1 0.39 0.393 4.20 0.037 0.120
HLA 2 0.52 0.261 2.79 0.049 0.407
Residuals 85 7.95 0.094 0.741 0.184
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.4 Parity
7.1.9.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.49 0.044 0.586
T1Dstatus 1 0.56 0.564 6.02 0.053 0.028 *
Days 1 0.12 0.117 1.24 0.011 0.088 .
seqRun 3 0.68 0.227 2.43 0.064 0.684
Age 1 0.41 0.413 4.41 0.039 0.340
Parity 1 0.24 0.236 2.52 0.022 0.732
BMI 1 0.30 0.302 3.22 0.028 0.788
Parity_Time_Interaction 1 0.08 0.076 0.81 0.007 0.157
Residuals 84 7.88 0.094 0.734 0.131
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.4.2 Parity (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.50 0.044 0.577
T1Dstatus 1 0.56 0.564 6.03 0.053 0.031 *
Days 1 0.12 0.117 1.25 0.011 0.096 .
seqRun 3 0.68 0.227 2.43 0.064 0.669
BMI 1 0.44 0.444 4.75 0.041 0.394
Age 1 0.37 0.375 4.01 0.035 0.451
Parity 1 0.13 0.132 1.41 0.012 0.942
Residuals 85 7.95 0.094 0.741 0.176
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.5 Mode of delivery
7.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.61 0.044 0.580
T1Dstatus 1 0.56 0.564 6.31 0.053 0.015 *
MOD 2 0.32 0.159 1.78 0.030 0.906
Days 1 0.12 0.119 1.33 0.011 0.095 .
seqRun 3 0.73 0.244 2.73 0.068 0.440
Age 1 0.59 0.592 6.62 0.055 0.013 *
Parity 1 0.22 0.222 2.48 0.021 0.765
BMI 1 0.31 0.310 3.47 0.029 0.662
MOD_Time_Interaction 1 0.07 0.074 0.83 0.007 0.988
Residuals 82 7.34 0.089 0.683 0.292
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.61 0.044 0.597
T1Dstatus 1 0.56 0.564 6.30 0.053 0.018 *
MOD 2 0.32 0.159 1.77 0.030 0.896
Days 1 0.12 0.119 1.32 0.011 0.088 .
seqRun 3 0.73 0.244 2.73 0.068 0.429
Age 1 0.59 0.592 6.61 0.055 0.015 *
Parity 1 0.22 0.222 2.48 0.021 0.747
BMI 1 0.31 0.310 3.46 0.029 0.655
MOD_Time_Interaction 1 0.07 0.067 0.75 0.006 0.998
Residuals 82 7.34 0.090 0.684 0.390
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.61 0.044 0.593
T1Dstatus 1 0.56 0.564 6.30 0.053 0.041 *
MOD 2 0.32 0.159 1.77 0.030 0.896
Days 1 0.12 0.119 1.32 0.011 0.080 .
seqRun 3 0.73 0.244 2.73 0.068 0.470
Age 1 0.59 0.592 6.61 0.055 0.018 *
Parity 1 0.22 0.222 2.48 0.021 0.755
BMI 1 0.31 0.310 3.46 0.029 0.640
MOD_Time_Interaction 1 0.07 0.066 0.74 0.006 0.997
Residuals 82 7.34 0.090 0.684 0.492
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.12 0.121 1.36 0.011 0.081 .
seqRun 3 0.73 0.243 2.72 0.068 0.707
Age 1 0.39 0.391 4.38 0.036 0.996
Parity 1 0.27 0.271 3.04 0.025 0.004 **
BMI 1 0.35 0.354 3.97 0.033 0.905
HLA 2 0.45 0.227 2.54 0.042 0.529
T1Dstatus 1 0.46 0.461 5.17 0.043 0.075 .
MOD 2 0.54 0.272 3.04 0.051 0.345
Residuals 83 7.41 0.089 0.690 0.198
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.6 Carbohydrate intake
7.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.53 0.044 0.574
T1Dstatus 1 0.56 0.564 6.11 0.053 0.032 *
Carbs 1 0.21 0.214 2.32 0.020 0.584
seqRun 3 0.68 0.228 2.46 0.064 0.667
Tri 2 0.11 0.055 0.60 0.010 0.638
Age 1 0.41 0.405 4.39 0.038 0.396
Parity 1 0.25 0.252 2.73 0.023 0.489
BMI 1 0.37 0.374 4.05 0.035 0.357
Carb_Time_Interaction 1 0.09 0.091 0.99 0.008 0.672
Residuals 82 7.57 0.092 0.705 0.266
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.52 0.044 0.614
T1Dstatus 1 0.56 0.564 6.07 0.053 0.023 *
Carbs 1 0.21 0.214 2.31 0.020 0.595
seqRun 3 0.68 0.228 2.45 0.064 0.686
Tri 2 0.11 0.055 0.59 0.010 0.601
Age 1 0.41 0.405 4.36 0.038 0.420
Parity 1 0.25 0.252 2.71 0.023 0.519
BMI 1 0.37 0.374 4.03 0.035 0.357
Carb_Time_Interaction 1 0.04 0.043 0.46 0.004 0.992
Residuals 82 7.62 0.093 0.710 0.379
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.52 0.044 0.59
T1Dstatus 1 0.56 0.564 6.08 0.053 0.03 *
Carbs 1 0.21 0.214 2.31 0.020 0.58
seqRun 3 0.68 0.228 2.45 0.064 0.66
Tri 2 0.11 0.055 0.59 0.010 0.62
Age 1 0.41 0.405 4.37 0.038 0.42
Parity 1 0.25 0.252 2.71 0.023 0.52
BMI 1 0.37 0.374 4.03 0.035 0.37
Carb_Time_Interaction 1 0.05 0.051 0.55 0.005 0.91
Residuals 82 7.61 0.093 0.709 0.31
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.6.4 Carbohydrate (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.74 0.247 2.68 0.069 0.016 *
Tri 2 0.11 0.055 0.60 0.010 0.693
Age 1 0.40 0.404 4.37 0.038 0.838
Parity 1 0.27 0.270 2.92 0.025 0.042 *
BMI 1 0.35 0.354 3.83 0.033 0.931
HLA 2 0.45 0.226 2.45 0.042 0.586
T1Dstatus 1 0.48 0.478 5.18 0.045 0.055 .
Carbs 1 0.26 0.262 2.84 0.024 0.358
Residuals 83 7.66 0.092 0.714 0.232
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.7 Fibre intake
7.1.9.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.47 0.044 0.567
T1Dstatus 1 0.56 0.564 5.97 0.053 0.024 *
Fiber 1 0.13 0.127 1.34 0.012 0.923
seqRun 3 0.66 0.221 2.33 0.062 0.758
Tri 2 0.11 0.057 0.60 0.011 0.583
Age 1 0.41 0.413 4.36 0.038 0.394
Parity 1 0.25 0.247 2.61 0.023 0.584
BMI 1 0.34 0.336 3.55 0.031 0.559
Fiber_Time_Interaction 1 0.05 0.053 0.56 0.005 0.766
Residuals 82 7.75 0.095 0.722 0.454
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.47 0.044 0.585
T1Dstatus 1 0.56 0.564 5.96 0.053 0.025 *
Fiber 1 0.13 0.127 1.34 0.012 0.899
seqRun 3 0.66 0.221 2.33 0.062 0.755
Tri 2 0.11 0.057 0.60 0.011 0.633
Age 1 0.41 0.413 4.35 0.038 0.366
Parity 1 0.25 0.247 2.60 0.023 0.570
BMI 1 0.34 0.336 3.54 0.031 0.566
Fiber_Time_Interaction 1 0.04 0.037 0.39 0.003 0.946
Residuals 82 7.77 0.095 0.724 0.516
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.47 0.234 2.47 0.044 0.567
T1Dstatus 1 0.56 0.564 5.96 0.053 0.028 *
Fiber 1 0.13 0.127 1.34 0.012 0.907
seqRun 3 0.66 0.221 2.33 0.062 0.779
Tri 2 0.11 0.057 0.60 0.011 0.609
Age 1 0.41 0.413 4.36 0.038 0.352
Parity 1 0.25 0.247 2.61 0.023 0.570
BMI 1 0.34 0.336 3.55 0.031 0.570
Fiber_Time_Interaction 1 0.05 0.048 0.51 0.004 0.701
Residuals 82 7.76 0.095 0.723 0.443
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.7.4 Fibre (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.74 0.247 2.63 0.069 0.021 *
Tri 2 0.11 0.055 0.59 0.010 0.670
Age 1 0.40 0.404 4.29 0.038 0.814
Parity 1 0.27 0.270 2.87 0.025 0.036 *
BMI 1 0.35 0.354 3.76 0.033 0.920
HLA 2 0.45 0.226 2.40 0.042 0.550
T1Dstatus 1 0.48 0.478 5.08 0.045 0.060 .
Fiber 1 0.12 0.120 1.28 0.011 0.883
Residuals 83 7.81 0.094 0.727 0.423
Total 95 10.74 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.8 1,5-AG (glucose control measurement)
7.1.9.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.50 0.248 2.75 0.048 0.518
T1Dstatus 1 0.63 0.632 7.00 0.062 0.015 *
Days 1 0.12 0.117 1.29 0.011 0.197
seqRun 3 0.62 0.208 2.31 0.061 0.865
Age 1 0.45 0.451 4.99 0.044 0.245
Parity 1 0.24 0.238 2.64 0.023 0.665
BMI 1 0.26 0.260 2.88 0.025 0.850
AG15 1 0.29 0.289 3.21 0.028 0.015 *
AG15_T1D_Interaction 1 0.18 0.179 1.98 0.018 0.779
Residuals 77 6.95 0.090 0.679 0.068 .
Total 89 10.24 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.29 0.146 2.39 0.072 0.778
Days 1 0.27 0.268 4.39 0.066 0.009 **
seqRun 3 0.64 0.214 3.51 0.158 0.780
Age 1 0.27 0.273 4.48 0.067 0.546
Parity 1 0.38 0.380 6.23 0.094 0.007 **
BMI 1 0.24 0.244 4.01 0.060 0.844
AG15 1 0.06 0.065 1.06 0.016 0.923
Residuals 31 1.89 0.061 0.466 0.390
Total 41 4.05 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.68 0.342 4.36 0.121 0.233
Days 1 0.13 0.128 1.62 0.023 0.058 .
seqRun 3 0.59 0.198 2.52 0.105 0.875
Age 1 0.78 0.776 9.89 0.138 0.067 .
Parity 1 0.13 0.135 1.72 0.024 0.952
BMI 1 0.20 0.199 2.54 0.035 0.660
AG15 1 0.22 0.225 2.86 0.040 0.771
Residuals 37 2.90 0.079 0.515 0.296
Total 47 5.64 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.2 Differential abundance analysis Genus taxonomic level
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 0 0 0 0 0 0 0 0 0 0
NotSig 113 113 113 113 113 113 113 113 113 113
Up 0 0 0 0 0 0 0 0 0 0
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 0 0
NotSig 113 113 113
Up 0 0 0No differentially abundant (i.e. all adjusted P-values > 0.1) genera were detected between T1D and non-T1D women accross trimesters or in each trimesters separatelly (i.e. nonT1D_vs_T1D, T1, T2 and T3 contrasts had no strains up or down). In addition no differences between trimesters were detected in samples from T1D and non-T1D women together or separatelly.
Results for contrasts with significant differentially abundant strains shown below
7.2.1 Across all trimesters (T1D vs non-T1D)
[1] "No DA taxa found"7.2.2 Only Trimester 1 (nonT1D vs T1D)
[1] "No DA taxa found"7.2.3 Only Trimester 2 (nonT1D vs T1D)
[1] "No DA taxa found"7.2.4 Only Trimester 3 (nonT1D vs T1D)
[1] "No DA taxa found"7.2.5 T1 vs T2 (All data)
[1] "No DA taxa found"7.2.6 T2 vs T3 (All data)
[1] "No DA taxa"7.2.7 T1 vs T3 (All data)
[1] "No DA taxa found"7.2.8 T1 vs T2 (in women with T1D)
[1] "No DA taxa found"7.2.9 T2 vs T3 (in women with T1D)
[1] "No DA taxa found"7.2.10 T1 vs T3 (in women with T1D)
[1] "No DA taxa found"7.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa found"7.2.12 T2 vs T3 (in women without T1D)
[1] "No DA taxa found"7.2.13 T1 vs T3 (in women without T1D)
[1] "No DA taxa found"8 Family taxonomic level
8.1 Microbial community composition analysis at Family level (Beta diversity analysis)
8.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.58 0.195 2.61 0.068 0.001 ***
Days 1 0.10 0.102 1.37 0.012 0.079 .
T1D_Time_Interaction 1 0.48 0.482 6.46 0.056 0.007 **
Age 1 0.29 0.292 3.91 0.034 0.990
Parity 1 0.18 0.177 2.38 0.021 0.006 **
BMI 1 0.17 0.167 2.24 0.020 0.989
HLA 2 0.41 0.204 2.73 0.048 0.339
T1Dstatus 1 0.07 0.067 0.90 0.008 0.943
Residuals 84 6.27 0.075 0.733 0.360
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.0078.1.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.267 0.0889 0.911 0.120 0.55
Nulliparous 1 0.174 0.1740 1.782 0.078 0.11
Age_LMP 1 0.128 0.1276 1.307 0.058 0.26
BMI_conception 1 0.081 0.0814 0.834 0.037 0.58
HLA.6DRML 2 0.174 0.0870 0.891 0.078 0.55
T1Dstatus 1 0.127 0.1265 1.296 0.057 0.26
Residuals 13 1.269 0.0976 0.572
Total 22 2.219 1.000 [1] 0.264Beta diversity Plot
8.1.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.343 0.1144 1.287 0.119 0.20
Nulliparous 1 0.077 0.0765 0.861 0.027 0.53
Age_LMP 1 0.116 0.1164 1.310 0.040 0.26
BMI_conception 1 0.114 0.1143 1.286 0.040 0.24
HLA.6DRML 2 0.173 0.0866 0.974 0.060 0.44
T1Dstatus 1 0.103 0.1033 1.162 0.036 0.32
Residuals 22 1.956 0.0889 0.678
Total 31 2.882 1.000 [1] 0.32Beta diversity Plot
8.1.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.167 0.0557 0.68 0.060 0.848
Nulliparous 1 0.104 0.1042 1.26 0.037 0.239
Age_LMP 1 0.108 0.1077 1.30 0.039 0.257
BMI_conception 1 0.187 0.1872 2.27 0.067 0.048 *
HLA.6DRML 2 0.120 0.0601 0.73 0.043 0.725
T1Dstatus 1 0.276 0.2756 3.34 0.099 0.006 **
Residuals 22 1.816 0.0826 0.654
Total 31 2.778 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.006Beta diversity Plot
8.1.5 Days within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.28 0.1400 3.05 0.080 0.530
seqRun 3 0.71 0.2360 5.14 0.203 0.476
Age 1 0.21 0.2128 4.63 0.061 0.504
Parity 1 0.28 0.2798 6.09 0.080 0.010 **
BMI 1 0.18 0.1771 3.85 0.051 0.818
Days 1 0.09 0.0905 1.97 0.026 0.051 .
Residuals 38 1.75 0.0459 0.500 0.038 *
Total 47 3.49 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
8.1.6 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.28 0.1400 3.01 0.080 0.550
seqRun 3 0.71 0.2360 5.08 0.203 0.484
Age 1 0.21 0.2128 4.58 0.061 0.466
Parity 1 0.28 0.2798 6.02 0.080 0.010 **
BMI 1 0.18 0.1771 3.81 0.051 0.829
Tri 2 0.12 0.0583 1.25 0.033 0.128
Residuals 37 1.72 0.0465 0.492 0.069 .
Total 47 3.49 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
8.1.7 Days within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.53 0.263 3.65 0.112 0.288
seqRun 3 0.38 0.127 1.76 0.081 0.946
Age 1 0.62 0.617 8.56 0.132 0.116
Parity 1 0.11 0.108 1.50 0.023 0.907
BMI 1 0.18 0.176 2.45 0.038 0.286
Days 1 0.13 0.131 1.82 0.028 0.025 *
Residuals 38 2.74 0.072 0.586 0.282
Total 47 4.68 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
8.1.8 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.53 0.263 3.56 0.112 0.29
seqRun 3 0.38 0.127 1.71 0.081 0.93
Age 1 0.62 0.617 8.35 0.132 0.12
Parity 1 0.11 0.108 1.47 0.023 0.92
BMI 1 0.18 0.176 2.39 0.038 0.28
Tri 2 0.14 0.068 0.92 0.029 0.26
Residuals 37 2.74 0.074 0.585 0.31
Total 47 4.68 1.000 Beta diversity Plot
8.1.9 Other factors
8.1.9.1 Age at conception
8.1.9.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.33 0.042 0.564
T1Dstatus 1 0.41 0.408 5.30 0.048 0.056 .
seqRun 3 0.61 0.203 2.64 0.071 0.342
Tri 2 0.09 0.046 0.59 0.011 0.587
Age 1 0.30 0.299 3.88 0.035 0.341
Parity 1 0.17 0.167 2.17 0.020 0.611
BMI 1 0.19 0.193 2.51 0.023 0.802
Age_Time_Interaction 1 0.03 0.033 0.43 0.004 0.747
Residuals 83 6.39 0.077 0.747 0.248
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.32 0.042 0.549
T1Dstatus 1 0.41 0.408 5.28 0.048 0.064 .
seqRun 3 0.61 0.203 2.63 0.071 0.339
Tri 2 0.09 0.046 0.59 0.011 0.571
Age 1 0.30 0.299 3.86 0.035 0.326
Parity 1 0.17 0.167 2.17 0.020 0.629
BMI 1 0.19 0.193 2.50 0.023 0.799
Age_Time_Interaction 1 0.01 0.010 0.13 0.001 0.982
Residuals 83 6.41 0.077 0.750 0.309
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.33 0.042 0.545
T1Dstatus 1 0.41 0.408 5.30 0.048 0.062 .
seqRun 3 0.61 0.203 2.64 0.071 0.338
Tri 2 0.09 0.046 0.59 0.011 0.572
Age 1 0.30 0.299 3.88 0.035 0.326
Parity 1 0.17 0.167 2.17 0.020 0.623
BMI 1 0.19 0.193 2.51 0.023 0.801
Age_Time_Interaction 1 0.04 0.035 0.46 0.004 0.639
Residuals 83 6.39 0.077 0.747 0.236
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.1.4 Age at conception (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.35 0.042 0.53
T1Dstatus 1 0.41 0.408 5.34 0.048 0.05 *
seqRun 3 0.61 0.203 2.65 0.071 0.33
Tri 2 0.09 0.046 0.60 0.011 0.54
Parity 1 0.15 0.145 1.90 0.017 0.72
BMI 1 0.25 0.248 3.25 0.029 0.68
Age 1 0.27 0.265 3.47 0.031 0.47
Residuals 84 6.42 0.076 0.751 0.20
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.2 Body max index (BMI)
8.1.9.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.32 0.042 0.555
T1Dstatus 1 0.41 0.408 5.28 0.048 0.057 .
seqRun 3 0.61 0.203 2.63 0.071 0.358
Tri 2 0.09 0.046 0.59 0.011 0.567
Age 1 0.30 0.299 3.87 0.035 0.295
Parity 1 0.17 0.167 2.17 0.020 0.627
BMI 1 0.19 0.193 2.50 0.023 0.797
BMI_Time_Interaction 1 0.01 0.011 0.14 0.001 0.957
Residuals 83 6.41 0.077 0.750 0.279
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.32 0.042 0.563
T1Dstatus 1 0.41 0.408 5.29 0.048 0.055 .
seqRun 3 0.61 0.203 2.63 0.071 0.328
Tri 2 0.09 0.046 0.59 0.011 0.545
Age 1 0.30 0.299 3.87 0.035 0.308
Parity 1 0.17 0.167 2.17 0.020 0.655
BMI 1 0.19 0.193 2.50 0.023 0.810
BMI_Time_Interaction 1 0.01 0.013 0.17 0.001 0.932
Residuals 83 6.41 0.077 0.750 0.246
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.2.3 BMI interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.33 0.042 0.53
T1Dstatus 1 0.41 0.408 5.31 0.048 0.06 .
seqRun 3 0.61 0.203 2.64 0.071 0.35
Tri 2 0.09 0.046 0.59 0.011 0.54
Age 1 0.30 0.299 3.88 0.035 0.34
Parity 1 0.17 0.167 2.18 0.020 0.61
BMI 1 0.19 0.193 2.51 0.023 0.81
BMI_Time_Interaction 1 0.04 0.040 0.53 0.005 0.34
Residuals 83 6.38 0.077 0.747 0.18
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.2.4 BMI (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.35 0.042 0.582
T1Dstatus 1 0.41 0.408 5.34 0.048 0.064 .
seqRun 3 0.61 0.203 2.65 0.071 0.359
Tri 2 0.09 0.046 0.60 0.011 0.542
Age 1 0.30 0.299 3.90 0.035 0.338
Parity 1 0.17 0.167 2.19 0.020 0.630
BMI 1 0.19 0.193 2.53 0.023 0.775
Residuals 84 6.42 0.076 0.751 0.234
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.3 HLA type
8.1.9.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.35 0.042 0.556
T1Dstatus 1 0.41 0.408 5.35 0.048 0.061 .
Days 1 0.11 0.110 1.44 0.013 0.075 .
seqRun 3 0.60 0.199 2.61 0.070 0.374
Age 1 0.29 0.286 3.75 0.034 0.368
Parity 1 0.16 0.164 2.15 0.019 0.700
BMI 1 0.19 0.188 2.46 0.022 0.818
HLA_Time_Interaction 1 0.03 0.026 0.35 0.003 1.000
Residuals 84 6.41 0.076 0.750 0.487
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.36 0.042 0.570
T1Dstatus 1 0.41 0.408 5.38 0.048 0.064 .
Days 1 0.11 0.110 1.45 0.013 0.074 .
seqRun 3 0.60 0.199 2.62 0.070 0.369
Age 1 0.29 0.286 3.77 0.034 0.402
Parity 1 0.16 0.164 2.16 0.019 0.708
BMI 1 0.19 0.188 2.47 0.022 0.816
HLA_Time_Interaction 1 0.06 0.059 0.78 0.007 0.998
Residuals 84 6.38 0.076 0.746 0.336
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.36 0.042 0.553
T1Dstatus 1 0.41 0.408 5.36 0.048 0.064 .
Days 1 0.11 0.110 1.44 0.013 0.064 .
seqRun 3 0.60 0.199 2.62 0.070 0.383
Age 1 0.29 0.286 3.76 0.034 0.388
Parity 1 0.16 0.164 2.15 0.019 0.677
BMI 1 0.19 0.188 2.47 0.022 0.838
HLA_Time_Interaction 1 0.04 0.039 0.51 0.005 0.829
Residuals 84 6.40 0.076 0.748 0.207
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.12 0.115 1.52 0.013 0.059 .
seqRun 3 0.57 0.190 2.51 0.067 0.852
Age 1 0.27 0.267 3.53 0.031 0.998
Parity 1 0.19 0.187 2.47 0.022 0.002 **
BMI 1 0.24 0.236 3.12 0.028 0.901
T1Dstatus 1 0.35 0.352 4.65 0.041 0.090 .
HLA 2 0.38 0.192 2.54 0.045 0.461
Residuals 85 6.43 0.076 0.753 0.168
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.4 Parity
8.1.9.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.37 0.042 0.543
T1Dstatus 1 0.41 0.408 5.39 0.048 0.062 .
Days 1 0.11 0.110 1.45 0.013 0.071 .
seqRun 3 0.60 0.199 2.63 0.070 0.393
Age 1 0.29 0.286 3.79 0.034 0.393
Parity 1 0.16 0.164 2.17 0.019 0.688
BMI 1 0.19 0.188 2.48 0.022 0.833
Parity_Time_Interaction 1 0.08 0.079 1.04 0.009 0.134
Residuals 84 6.36 0.076 0.744 0.138
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.4.2 Parity (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.37 0.042 0.550
T1Dstatus 1 0.41 0.408 5.39 0.048 0.066 .
Days 1 0.11 0.110 1.45 0.013 0.069 .
seqRun 3 0.60 0.199 2.63 0.070 0.374
BMI 1 0.31 0.306 4.04 0.036 0.481
Age 1 0.25 0.248 3.27 0.029 0.450
Parity 1 0.09 0.085 1.12 0.010 0.951
Residuals 85 6.43 0.076 0.753 0.174
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.5 Mode of delivery
8.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.51 0.042 0.544
T1Dstatus 1 0.41 0.408 5.70 0.048 0.064 .
MOD 2 0.31 0.155 2.16 0.036 0.675
Days 1 0.11 0.111 1.55 0.013 0.054 .
seqRun 3 0.59 0.198 2.77 0.069 0.378
Age 1 0.49 0.486 6.79 0.057 0.005 **
Parity 1 0.15 0.150 2.09 0.017 0.781
BMI 1 0.20 0.202 2.82 0.024 0.675
MOD_Time_Interaction 1 0.06 0.061 0.86 0.007 0.990
Residuals 82 5.87 0.072 0.686 0.180
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.50 0.042 0.565
T1Dstatus 1 0.41 0.408 5.69 0.048 0.057 .
MOD 2 0.31 0.155 2.16 0.036 0.686
Days 1 0.11 0.111 1.54 0.013 0.062 .
seqRun 3 0.59 0.198 2.76 0.069 0.409
Age 1 0.49 0.486 6.78 0.057 0.004 **
Parity 1 0.15 0.150 2.09 0.017 0.752
BMI 1 0.20 0.202 2.81 0.024 0.666
MOD_Time_Interaction 1 0.05 0.051 0.71 0.006 1.000
Residuals 82 5.88 0.072 0.688 0.302
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.50 0.042 0.575
T1Dstatus 1 0.41 0.408 5.70 0.048 0.068 .
MOD 2 0.31 0.155 2.16 0.036 0.685
Days 1 0.11 0.111 1.54 0.013 0.050 *
seqRun 3 0.59 0.198 2.76 0.069 0.383
Age 1 0.49 0.486 6.78 0.057 0.005 **
Parity 1 0.15 0.150 2.09 0.017 0.763
BMI 1 0.20 0.202 2.81 0.024 0.667
MOD_Time_Interaction 1 0.05 0.053 0.74 0.006 0.999
Residuals 82 5.88 0.072 0.687 0.390
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.12 0.115 1.61 0.013 0.069 .
seqRun 3 0.57 0.190 2.67 0.067 0.827
Age 1 0.27 0.267 3.74 0.031 0.994
Parity 1 0.19 0.187 2.62 0.022 0.002 **
BMI 1 0.24 0.236 3.30 0.028 0.885
HLA 2 0.34 0.172 2.41 0.040 0.532
T1Dstatus 1 0.39 0.391 5.48 0.046 0.070 .
MOD 2 0.51 0.253 3.54 0.059 0.223
Residuals 83 5.93 0.071 0.694 0.117
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.6 Carbohydrate intake
8.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.44 0.042 0.57
T1Dstatus 1 0.41 0.408 5.54 0.048 0.06 .
Carbs 1 0.25 0.246 3.35 0.029 0.26
seqRun 3 0.61 0.204 2.77 0.072 0.34
Tri 2 0.09 0.043 0.59 0.010 0.59
Age 1 0.28 0.276 3.75 0.032 0.47
Parity 1 0.18 0.184 2.49 0.021 0.37
BMI 1 0.26 0.264 3.59 0.031 0.30
Carb_Time_Interaction 1 0.07 0.073 1.00 0.009 0.77
Residuals 82 6.04 0.074 0.706 0.16
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.43 0.042 0.523
T1Dstatus 1 0.41 0.408 5.52 0.048 0.065 .
Carbs 1 0.25 0.246 3.33 0.029 0.266
seqRun 3 0.61 0.204 2.76 0.072 0.371
Tri 2 0.09 0.043 0.59 0.010 0.598
Age 1 0.28 0.276 3.73 0.032 0.464
Parity 1 0.18 0.184 2.48 0.021 0.370
BMI 1 0.26 0.264 3.57 0.031 0.292
Carb_Time_Interaction 1 0.04 0.044 0.59 0.005 0.972
Residuals 82 6.07 0.074 0.710 0.214
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.43 0.042 0.541
T1Dstatus 1 0.41 0.408 5.52 0.048 0.042 *
Carbs 1 0.25 0.246 3.33 0.029 0.294
seqRun 3 0.61 0.204 2.76 0.072 0.344
Tri 2 0.09 0.043 0.59 0.010 0.592
Age 1 0.28 0.276 3.74 0.032 0.450
Parity 1 0.18 0.184 2.48 0.021 0.387
BMI 1 0.26 0.264 3.57 0.031 0.319
Carb_Time_Interaction 1 0.05 0.048 0.64 0.006 0.894
Residuals 82 6.06 0.074 0.709 0.172
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.6.4 Carbohydrate (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.58 0.195 2.64 0.068 0.001 ***
Tri 2 0.08 0.042 0.58 0.010 0.637
Age 1 0.28 0.279 3.79 0.033 0.850
Parity 1 0.19 0.186 2.53 0.022 0.021 *
BMI 1 0.24 0.235 3.20 0.028 0.901
HLA 2 0.35 0.173 2.35 0.041 0.566
T1Dstatus 1 0.41 0.410 5.57 0.048 0.043 *
Carbs 1 0.31 0.310 4.21 0.036 0.140
Residuals 83 6.11 0.074 0.715 0.120
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.7 Fibre intake
8.1.9.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.35 0.042 0.573
T1Dstatus 1 0.41 0.408 5.33 0.048 0.048 *
Fiber 1 0.13 0.132 1.72 0.015 0.711
seqRun 3 0.59 0.197 2.58 0.069 0.418
Tri 2 0.09 0.046 0.60 0.011 0.542
Age 1 0.27 0.269 3.52 0.031 0.493
Parity 1 0.17 0.175 2.29 0.020 0.506
BMI 1 0.22 0.220 2.88 0.026 0.588
Fiber_Time_Interaction 1 0.03 0.027 0.35 0.003 0.929
Residuals 82 6.27 0.077 0.734 0.436
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.35 0.042 0.551
T1Dstatus 1 0.41 0.408 5.34 0.048 0.043 *
Fiber 1 0.13 0.132 1.72 0.015 0.716
seqRun 3 0.59 0.197 2.58 0.069 0.411
Tri 2 0.09 0.046 0.60 0.011 0.515
Age 1 0.27 0.269 3.52 0.031 0.512
Parity 1 0.17 0.175 2.29 0.020 0.489
BMI 1 0.22 0.220 2.88 0.026 0.595
Fiber_Time_Interaction 1 0.03 0.034 0.44 0.004 0.876
Residuals 82 6.27 0.076 0.733 0.416
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.36 0.179 2.35 0.042 0.596
T1Dstatus 1 0.41 0.408 5.35 0.048 0.052 .
Fiber 1 0.13 0.132 1.72 0.015 0.704
seqRun 3 0.59 0.197 2.58 0.069 0.401
Tri 2 0.09 0.046 0.60 0.011 0.538
Age 1 0.27 0.269 3.53 0.031 0.470
Parity 1 0.17 0.175 2.29 0.020 0.491
BMI 1 0.22 0.220 2.88 0.026 0.586
Fiber_Time_Interaction 1 0.04 0.040 0.53 0.005 0.708
Residuals 82 6.26 0.076 0.732 0.395
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.7.4 Fibre (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.58 0.195 2.57 0.068 0.001 ***
Tri 2 0.08 0.042 0.56 0.010 0.626
Age 1 0.28 0.279 3.67 0.033 0.848
Parity 1 0.19 0.186 2.45 0.022 0.018 *
BMI 1 0.24 0.235 3.10 0.028 0.916
HLA 2 0.35 0.173 2.28 0.041 0.555
T1Dstatus 1 0.41 0.410 5.40 0.048 0.048 *
Fiber 1 0.12 0.121 1.59 0.014 0.733
Residuals 83 6.30 0.076 0.737 0.341
Total 95 8.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.8 1,5-AG (glucose control measurement)
8.1.9.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.38 0.189 2.53 0.046 0.532
T1Dstatus 1 0.49 0.491 6.59 0.060 0.027 *
Days 1 0.11 0.113 1.51 0.014 0.112
seqRun 3 0.53 0.177 2.37 0.065 0.675
Age 1 0.32 0.316 4.23 0.038 0.272
Parity 1 0.17 0.174 2.33 0.021 0.570
BMI 1 0.15 0.150 2.01 0.018 0.895
AG15 1 0.22 0.225 3.02 0.027 0.028 *
AG15_T1D_Interaction 1 0.10 0.101 1.35 0.012 0.954
Residuals 77 5.74 0.075 0.699 0.107
Total 89 8.21 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.245 0.1226 2.66 0.080 0.606
Days 1 0.221 0.2209 4.80 0.072 0.015 *
seqRun 3 0.591 0.1969 4.28 0.192 0.702
Age 1 0.121 0.1211 2.63 0.039 0.680
Parity 1 0.302 0.3017 6.56 0.098 0.003 **
BMI 1 0.138 0.1377 2.99 0.045 0.894
AG15 1 0.031 0.0307 0.67 0.010 0.980
Residuals 31 1.427 0.0460 0.464 0.216
Total 41 3.075 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.9.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.53 0.263 3.79 0.112 0.283
Days 1 0.14 0.137 1.97 0.029 0.031 *
seqRun 3 0.39 0.129 1.85 0.083 0.910
Age 1 0.61 0.610 8.78 0.130 0.116
Parity 1 0.11 0.115 1.65 0.025 0.891
BMI 1 0.16 0.165 2.37 0.035 0.368
AG15 1 0.17 0.170 2.45 0.036 0.807
Residuals 37 2.57 0.070 0.549 0.408
Total 47 4.68 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.2 Differential abundance analysis Family taxonomic level
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 0 0 0 0 0 0 0 0 0 0
NotSig 52 52 52 52 52 52 51 52 52 52
Up 0 0 0 0 0 0 1 0 0 0
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 0 0
NotSig 52 22 52
Up 0 30 0Results for contrasts with significant (or borderline significant) differences shown below
8.2.1 Across all trimesters (T1D vs non-T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
2 Enterobacteriaceae -0.897 0.00342 0.0890 0.146 97.9 1.186 100.0
1 Prevotellaceae 1.253 0.00097 0.0504 5.199 100.0 0.957 97.9[1] 308.2.2 Only Trimester 1 (nonT1D vs T1D)
[1] "No DA taxa found"8.2.3 Only Trimester 2 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Prevotellaceae 1.39 0.00124 0.0647 5.25 100.0
2 Prevotellaceae 1.39 0.00124 0.0647 1.28 93.88.2.4 Only Trimester 3 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Bacteroidaceae -1.32 0.0015 0.0778 18.8 100
2 Bacteroidaceae -1.32 0.0015 0.0778 34.1 100[1] 318.2.5 T1 vs T2 (All data)
[1] "No DA taxa found"8.2.6 T2 vs T3 (All data)
[1] "No DA taxa"8.2.7 T1 vs T3 (All data)
[1] Classification LogFC P.Val adj.P.Val mean%
[6] Prev%
<0 rows> (or 0-length row.names)8.2.8 T1 vs T2 (in women with T1D)
[1] "No DA taxa found"8.2.9 T2 vs T3 (in women with T1D)
[1] "No DA taxa found"8.2.10 T1 vs T3 (in women with T1D)
[1] "No DA taxa found"8.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa found"8.2.12 T2 vs T3 (in women without T1D)
Classification LogFC P.Val adj.P.Val T2:mean% T2Prev% T3:mean% T3Prev%
1 Pasteurellaceae 0.549 0.000819 0.0391 0.177 70 0.052 52.9[1] 158.2.13 T1 vs T3 (in women without T1D)
[1] "No DA taxa found"9 Order taxonomic level
9.1 Microbial community composition analysis at Order level (Beta diversity analysis)
9.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.39 0.131 3.44 0.094 0.001 ***
Days 1 0.01 0.007 0.18 0.002 0.829
T1D_Time_Interaction 1 0.33 0.331 8.71 0.079 0.023 *
Age 1 0.05 0.049 1.29 0.012 0.402
Parity 1 0.06 0.055 1.46 0.013 0.514
BMI 1 0.06 0.058 1.54 0.014 0.836
HLA 2 0.07 0.033 0.86 0.016 0.820
T1Dstatus 1 0.03 0.029 0.77 0.007 0.713
Residuals 84 3.19 0.038 0.764 0.668
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.0239.1.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.129 0.0430 1.10 0.124 0.356
Nulliparous 1 0.241 0.2415 6.20 0.232 0.009 **
Age_LMP 1 0.020 0.0199 0.51 0.019 0.565
BMI_conception 1 0.010 0.0098 0.25 0.009 0.845
HLA.6DRML 2 0.058 0.0290 0.74 0.056 0.533
T1Dstatus 1 0.076 0.0764 1.96 0.073 0.156
Residuals 13 0.507 0.0390 0.487
Total 22 1.041 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.156Beta diversity Plot
9.1.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.185 0.0618 1.287 0.130 0.29
Nulliparous 1 0.016 0.0162 0.337 0.011 0.69
Age_LMP 1 0.020 0.0197 0.411 0.014 0.64
BMI_conception 1 0.072 0.0719 1.498 0.051 0.21
HLA.6DRML 2 0.010 0.0051 0.107 0.007 0.99
T1Dstatus 1 0.062 0.0622 1.296 0.044 0.24
Residuals 22 1.057 0.0480 0.743
Total 31 1.422 1.000 [1] 0.239Beta diversity Plot
9.1.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.099 0.0331 0.88 0.077 0.497
Nulliparous 1 0.031 0.0313 0.83 0.024 0.410
Age_LMP 1 0.033 0.0329 0.87 0.026 0.377
BMI_conception 1 0.120 0.1195 3.18 0.093 0.061 .
HLA.6DRML 2 0.018 0.0092 0.24 0.014 0.950
T1Dstatus 1 0.157 0.1574 4.19 0.122 0.032 *
Residuals 22 0.827 0.0376 0.643
Total 31 1.286 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.032Beta diversity Plot
9.1.5 Days within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.063 0.0315 1.48 0.048 0.69
seqRun 3 0.269 0.0896 4.20 0.205 0.45
Age 1 0.065 0.0655 3.07 0.050 0.67
Parity 1 0.044 0.0443 2.08 0.034 0.22
BMI 1 0.030 0.0296 1.39 0.023 0.62
Days 1 0.030 0.0297 1.39 0.023 0.20
Residuals 38 0.811 0.0214 0.618 0.64
Total 47 1.312 1.000 Beta diversity Plot
9.1.6 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.063 0.0315 1.49 0.048 0.70
seqRun 3 0.269 0.0896 4.24 0.205 0.46
Age 1 0.065 0.0655 3.10 0.050 0.68
Parity 1 0.044 0.0443 2.10 0.034 0.23
BMI 1 0.030 0.0296 1.40 0.023 0.60
Tri 2 0.059 0.0293 1.38 0.045 0.18
Residuals 37 0.782 0.0211 0.596 0.53
Total 47 1.312 1.000 Beta diversity Plot
9.1.7 Days within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.285 0.143 3.21 0.112 0.336
seqRun 3 0.147 0.049 1.10 0.058 0.955
Age 1 0.318 0.318 7.15 0.125 0.068 .
Parity 1 0.028 0.028 0.63 0.011 0.945
BMI 1 0.018 0.018 0.40 0.007 0.889
Days 1 0.061 0.061 1.36 0.024 0.153
Residuals 38 1.691 0.045 0.664 0.523
Total 47 2.548 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
9.1.8 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.285 0.143 3.10 0.112 0.333
seqRun 3 0.147 0.049 1.07 0.058 0.968
Age 1 0.318 0.318 6.91 0.125 0.087 .
Parity 1 0.028 0.028 0.61 0.011 0.917
BMI 1 0.018 0.018 0.39 0.007 0.885
Tri 2 0.049 0.024 0.53 0.019 0.525
Residuals 37 1.703 0.046 0.668 0.615
Total 47 2.548 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
9.1.9 Other factors
9.1.9.1 Age at conception
9.1.9.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.96 0.018 0.826
T1Dstatus 1 0.31 0.3066 7.89 0.073 0.068 .
seqRun 3 0.34 0.1123 2.89 0.081 0.622
Tri 2 0.04 0.0194 0.50 0.009 0.582
Age 1 0.05 0.0453 1.17 0.011 0.358
Parity 1 0.06 0.0611 1.57 0.015 0.259
BMI 1 0.05 0.0534 1.37 0.013 0.853
Age_Time_Interaction 1 0.04 0.0354 0.91 0.008 0.274
Residuals 83 3.22 0.0388 0.772 0.426
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.95 0.018 0.817
T1Dstatus 1 0.31 0.3066 7.82 0.073 0.038 *
seqRun 3 0.34 0.1123 2.86 0.081 0.623
Tri 2 0.04 0.0194 0.49 0.009 0.606
Age 1 0.05 0.0453 1.16 0.011 0.320
Parity 1 0.06 0.0611 1.56 0.015 0.255
BMI 1 0.05 0.0534 1.36 0.013 0.876
Age_Time_Interaction 1 0.00 0.0032 0.08 0.001 0.894
Residuals 83 3.26 0.0392 0.780 0.502
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.97 0.018 0.790
T1Dstatus 1 0.31 0.3066 7.94 0.073 0.044 *
seqRun 3 0.34 0.1123 2.91 0.081 0.643
Tri 2 0.04 0.0194 0.50 0.009 0.586
Age 1 0.05 0.0453 1.17 0.011 0.329
Parity 1 0.06 0.0611 1.58 0.015 0.278
BMI 1 0.05 0.0534 1.38 0.013 0.873
Age_Time_Interaction 1 0.05 0.0549 1.42 0.013 0.169
Residuals 83 3.21 0.0386 0.767 0.401
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.1.4 Age at conception (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.96 0.018 0.826
T1Dstatus 1 0.31 0.3066 7.90 0.073 0.056 .
seqRun 3 0.34 0.1123 2.89 0.081 0.608
Tri 2 0.04 0.0194 0.50 0.009 0.596
Parity 1 0.06 0.0636 1.64 0.015 0.215
BMI 1 0.05 0.0477 1.23 0.011 0.887
Age 1 0.05 0.0486 1.25 0.012 0.492
Residuals 84 3.26 0.0388 0.780 0.431
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.2 Body max index (BMI)
9.1.9.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.96 0.018 0.824
T1Dstatus 1 0.31 0.3066 7.85 0.073 0.045 *
seqRun 3 0.34 0.1123 2.87 0.081 0.628
Tri 2 0.04 0.0194 0.50 0.009 0.582
Age 1 0.05 0.0453 1.16 0.011 0.335
Parity 1 0.06 0.0611 1.57 0.015 0.266
BMI 1 0.05 0.0534 1.37 0.013 0.859
BMI_Time_Interaction 1 0.02 0.0191 0.49 0.005 0.473
Residuals 83 3.24 0.0390 0.776 0.482
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.95 0.018 0.818
T1Dstatus 1 0.31 0.3066 7.81 0.073 0.059 .
seqRun 3 0.34 0.1123 2.86 0.081 0.635
Tri 2 0.04 0.0194 0.49 0.009 0.617
Age 1 0.05 0.0453 1.16 0.011 0.323
Parity 1 0.06 0.0611 1.56 0.015 0.288
BMI 1 0.05 0.0534 1.36 0.013 0.882
BMI_Time_Interaction 1 0.00 0.0028 0.07 0.001 0.882
Residuals 83 3.26 0.0392 0.780 0.503
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.2.3 BMI interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.96 0.018 0.82
T1Dstatus 1 0.31 0.3066 7.86 0.073 0.06 .
seqRun 3 0.34 0.1123 2.88 0.081 0.61
Tri 2 0.04 0.0194 0.50 0.009 0.60
Age 1 0.05 0.0453 1.16 0.011 0.32
Parity 1 0.06 0.0611 1.57 0.015 0.27
BMI 1 0.05 0.0534 1.37 0.013 0.86
BMI_Time_Interaction 1 0.02 0.0203 0.52 0.005 0.34
Residuals 83 3.24 0.0390 0.776 0.45
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.2.4 BMI (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.96 0.018 0.817
T1Dstatus 1 0.31 0.3066 7.90 0.073 0.057 .
seqRun 3 0.34 0.1123 2.89 0.081 0.643
Tri 2 0.04 0.0194 0.50 0.009 0.591
Age 1 0.05 0.0453 1.17 0.011 0.311
Parity 1 0.06 0.0611 1.58 0.015 0.256
BMI 1 0.05 0.0534 1.38 0.013 0.876
Residuals 84 3.26 0.0388 0.780 0.435
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.3 HLA type
9.1.9.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.96 0.018 0.807
T1Dstatus 1 0.31 0.3066 7.85 0.073 0.059 .
Days 1 0.01 0.0066 0.17 0.002 0.848
seqRun 3 0.33 0.1114 2.85 0.080 0.643
Age 1 0.04 0.0442 1.13 0.011 0.341
Parity 1 0.06 0.0598 1.53 0.014 0.304
BMI 1 0.06 0.0595 1.52 0.014 0.858
HLA_Time_Interaction 1 0.01 0.0115 0.30 0.003 0.658
Residuals 84 3.28 0.0390 0.785 0.484
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.96 0.018 0.810
T1Dstatus 1 0.31 0.3066 7.85 0.073 0.044 *
Days 1 0.01 0.0066 0.17 0.002 0.837
seqRun 3 0.33 0.1114 2.85 0.080 0.611
Age 1 0.04 0.0442 1.13 0.011 0.331
Parity 1 0.06 0.0598 1.53 0.014 0.301
BMI 1 0.06 0.0595 1.52 0.014 0.850
HLA_Time_Interaction 1 0.01 0.0094 0.24 0.002 0.948
Residuals 84 3.28 0.0391 0.786 0.534
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.95 0.018 0.81
T1Dstatus 1 0.31 0.3066 7.83 0.073 0.07 .
Days 1 0.01 0.0066 0.17 0.002 0.85
seqRun 3 0.33 0.1114 2.84 0.080 0.62
Age 1 0.04 0.0442 1.13 0.011 0.34
Parity 1 0.06 0.0598 1.53 0.014 0.30
BMI 1 0.06 0.0595 1.52 0.014 0.84
HLA_Time_Interaction 1 0.00 0.0003 0.01 0.000 0.98
Residuals 84 3.29 0.0392 0.788 0.51
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.01 0.0123 0.32 0.003 0.687
seqRun 3 0.39 0.1288 3.33 0.092 0.562
Age 1 0.04 0.0374 0.97 0.009 0.605
Parity 1 0.05 0.0533 1.38 0.013 0.309
BMI 1 0.12 0.1178 3.04 0.028 0.337
T1Dstatus 1 0.21 0.2123 5.48 0.051 0.095 .
HLA 2 0.07 0.0332 0.86 0.016 0.820
Residuals 85 3.29 0.0387 0.788 0.434
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.4 Parity
9.1.9.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.97 0.018 0.796
T1Dstatus 1 0.31 0.3066 8.00 0.073 0.045 *
Days 1 0.01 0.0066 0.17 0.002 0.851
seqRun 3 0.33 0.1114 2.91 0.080 0.639
Age 1 0.04 0.0442 1.15 0.011 0.321
Parity 1 0.06 0.0598 1.56 0.014 0.284
BMI 1 0.06 0.0595 1.55 0.014 0.853
Parity_Time_Interaction 1 0.07 0.0721 1.88 0.017 0.061 .
Residuals 84 3.22 0.0383 0.771 0.332
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.4.2 Parity (no interaction but within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.062 0.0310 0.68 0.059 0.595
T1Dstatus 1 0.013 0.0129 0.29 0.012 0.829
seqRun 1 0.086 0.0858 1.89 0.082 0.051 .
Age 1 0.036 0.0357 0.79 0.034 0.716
BMI 1 0.018 0.0181 0.40 0.017 0.768
Parity 1 0.148 0.1477 3.26 0.142 0.485
Residuals 15 0.679 0.0453 0.652 0.744
Total 22 1.041 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.4.3 Parity (no interaction but within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.023 0.0113 0.26 0.013 0.944
T1Dstatus 1 0.223 0.2234 5.11 0.128 0.037 *
seqRun 1 0.052 0.0518 1.18 0.030 0.926
Age 1 0.013 0.0126 0.29 0.007 0.245
BMI 1 0.021 0.0213 0.49 0.012 0.424
Parity 1 0.018 0.0178 0.41 0.010 0.824
Residuals 32 1.400 0.0437 0.800 0.556
Total 39 1.749 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.4.4 Parity (no interaction but within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.032 0.0161 0.41 0.024 0.853
T1Dstatus 1 0.193 0.1932 4.93 0.142 0.028 *
seqRun 1 0.015 0.0153 0.39 0.011 0.859
Age 1 0.028 0.0279 0.71 0.021 0.714
BMI 1 0.035 0.0354 0.90 0.026 0.757
Parity 1 0.073 0.0735 1.87 0.054 0.757
Residuals 25 0.980 0.0392 0.722 0.313
Total 32 1.357 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.5 Mode of delivery
9.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.99 0.018 0.820
T1Dstatus 1 0.31 0.3066 8.11 0.073 0.054 .
MOD 2 0.13 0.0645 1.71 0.031 0.584
Days 1 0.01 0.0057 0.15 0.001 0.863
seqRun 3 0.28 0.0946 2.50 0.068 0.695
Age 1 0.09 0.0913 2.41 0.022 0.076 .
Parity 1 0.07 0.0653 1.73 0.016 0.290
BMI 1 0.09 0.0868 2.29 0.021 0.597
MOD_Time_Interaction 1 0.03 0.0322 0.85 0.008 0.685
Residuals 82 3.10 0.0378 0.743 0.552
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.98 0.018 0.829
T1Dstatus 1 0.31 0.3066 8.05 0.073 0.047 *
MOD 2 0.13 0.0645 1.69 0.031 0.572
Days 1 0.01 0.0057 0.15 0.001 0.881
seqRun 3 0.28 0.0946 2.48 0.068 0.688
Age 1 0.09 0.0913 2.40 0.022 0.076 .
Parity 1 0.07 0.0653 1.71 0.016 0.287
BMI 1 0.09 0.0868 2.28 0.021 0.608
MOD_Time_Interaction 1 0.01 0.0111 0.29 0.003 0.994
Residuals 82 3.12 0.0381 0.748 0.729
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.99 0.018 0.817
T1Dstatus 1 0.31 0.3066 8.09 0.073 0.059 .
MOD 2 0.13 0.0645 1.70 0.031 0.573
Days 1 0.01 0.0057 0.15 0.001 0.883
seqRun 3 0.28 0.0946 2.50 0.068 0.700
Age 1 0.09 0.0913 2.41 0.022 0.079 .
Parity 1 0.07 0.0653 1.72 0.016 0.281
BMI 1 0.09 0.0868 2.29 0.021 0.601
MOD_Time_Interaction 1 0.03 0.0256 0.68 0.006 0.958
Residuals 82 3.11 0.0379 0.744 0.721
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.01 0.0123 0.33 0.003 0.687
seqRun 3 0.39 0.1288 3.41 0.092 0.563
Age 1 0.04 0.0374 0.99 0.009 0.625
Parity 1 0.05 0.0533 1.41 0.013 0.288
BMI 1 0.12 0.1178 3.12 0.028 0.338
HLA 2 0.04 0.0210 0.56 0.010 0.941
T1Dstatus 1 0.24 0.2365 6.27 0.057 0.076 .
MOD 2 0.16 0.0787 2.09 0.038 0.476
Residuals 83 3.13 0.0378 0.750 0.547
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.6 Carbohydrate intake
9.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 1.03 0.018 0.796
T1Dstatus 1 0.31 0.3066 8.46 0.073 0.060 .
Carbs 1 0.04 0.0403 1.11 0.010 0.611
seqRun 3 0.40 0.1317 3.64 0.095 0.351
Tri 2 0.03 0.0170 0.47 0.008 0.645
Age 1 0.10 0.1031 2.85 0.025 0.042 *
Parity 1 0.08 0.0768 2.12 0.018 0.138
BMI 1 0.10 0.0976 2.69 0.023 0.511
Carb_Time_Interaction 1 0.08 0.0773 2.13 0.019 0.465
Residuals 82 2.97 0.0362 0.711 0.257
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 1.01 0.018 0.804
T1Dstatus 1 0.31 0.3066 8.30 0.073 0.058 .
Carbs 1 0.04 0.0403 1.09 0.010 0.628
seqRun 3 0.40 0.1317 3.57 0.095 0.352
Tri 2 0.03 0.0170 0.46 0.008 0.644
Age 1 0.10 0.1031 2.79 0.025 0.051 .
Parity 1 0.08 0.0768 2.08 0.018 0.119
BMI 1 0.10 0.0976 2.64 0.023 0.526
Carb_Time_Interaction 1 0.02 0.0197 0.53 0.005 0.933
Residuals 82 3.03 0.0369 0.725 0.431
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 1.02 0.018 0.804
T1Dstatus 1 0.31 0.3066 8.35 0.073 0.049 *
Carbs 1 0.04 0.0403 1.10 0.010 0.612
seqRun 3 0.40 0.1317 3.59 0.095 0.332
Tri 2 0.03 0.0170 0.46 0.008 0.631
Age 1 0.10 0.1031 2.81 0.025 0.047 *
Parity 1 0.08 0.0768 2.09 0.018 0.115
BMI 1 0.10 0.0976 2.66 0.023 0.536
Carb_Time_Interaction 1 0.04 0.0387 1.05 0.009 0.697
Residuals 82 3.01 0.0367 0.721 0.305
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.6.4 Carbohydrate (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.39 0.1306 3.56 0.094 0.001 ***
Tri 2 0.04 0.0183 0.50 0.009 0.600
Age 1 0.04 0.0381 1.04 0.009 0.589
Parity 1 0.05 0.0527 1.43 0.013 0.583
BMI 1 0.11 0.1075 2.93 0.026 0.577
HLA 2 0.04 0.0196 0.53 0.009 0.948
T1Dstatus 1 0.25 0.2509 6.83 0.060 0.085 .
Carbs 1 0.21 0.2116 5.76 0.051 0.104
Residuals 83 3.05 0.0367 0.730 0.238
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.7 Fibre intake
9.1.9.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.97 0.018 0.807
T1Dstatus 1 0.31 0.3066 7.93 0.073 0.048 *
Fiber 1 0.00 0.0048 0.12 0.001 0.992
seqRun 3 0.35 0.1164 3.01 0.084 0.523
Tri 2 0.04 0.0193 0.50 0.009 0.595
Age 1 0.07 0.0658 1.70 0.016 0.176
Parity 1 0.07 0.0704 1.82 0.017 0.196
BMI 1 0.07 0.0680 1.76 0.016 0.731
Fiber_Time_Interaction 1 0.03 0.0261 0.67 0.006 0.469
Residuals 82 3.17 0.0387 0.760 0.547
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.96 0.018 0.828
T1Dstatus 1 0.31 0.3066 7.87 0.073 0.057 .
Fiber 1 0.00 0.0048 0.12 0.001 0.995
seqRun 3 0.35 0.1164 2.99 0.084 0.511
Tri 2 0.04 0.0193 0.49 0.009 0.569
Age 1 0.07 0.0658 1.69 0.016 0.157
Parity 1 0.07 0.0704 1.81 0.017 0.194
BMI 1 0.07 0.0680 1.75 0.016 0.715
Fiber_Time_Interaction 1 0.00 0.0040 0.10 0.001 0.950
Residuals 82 3.19 0.0390 0.765 0.664
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0373 0.96 0.018 0.80
T1Dstatus 1 0.31 0.3066 7.90 0.073 0.05 *
Fiber 1 0.00 0.0048 0.12 0.001 0.99
seqRun 3 0.35 0.1164 3.00 0.084 0.52
Tri 2 0.04 0.0193 0.50 0.009 0.60
Age 1 0.07 0.0658 1.70 0.016 0.16
Parity 1 0.07 0.0704 1.81 0.017 0.18
BMI 1 0.07 0.0680 1.75 0.016 0.72
Fiber_Time_Interaction 1 0.02 0.0157 0.40 0.004 0.61
Residuals 82 3.18 0.0388 0.762 0.54
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.7.4 Fibre (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.39 0.1306 3.39 0.094 0.001 ***
Tri 2 0.04 0.0183 0.47 0.009 0.632
Age 1 0.04 0.0381 0.99 0.009 0.588
Parity 1 0.05 0.0527 1.37 0.013 0.605
BMI 1 0.11 0.1075 2.79 0.026 0.558
HLA 2 0.04 0.0196 0.51 0.009 0.946
T1Dstatus 1 0.25 0.2509 6.51 0.060 0.082 .
Fiber 1 0.06 0.0614 1.59 0.015 0.462
Residuals 83 3.20 0.0385 0.766 0.501
Total 95 4.18 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.8 1,5-AG (glucose control measurement)
9.1.9.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.12 0.059 1.59 0.029 0.636
T1Dstatus 1 0.37 0.368 9.89 0.091 0.035 *
Days 1 0.00 0.001 0.03 0.000 0.961
seqRun 3 0.28 0.092 2.48 0.068 0.788
Age 1 0.06 0.065 1.74 0.016 0.273
Parity 1 0.06 0.058 1.56 0.014 0.263
BMI 1 0.04 0.036 0.97 0.009 0.903
AG15 1 0.18 0.181 4.87 0.045 0.005 **
AG15_T1D_Interaction 1 0.08 0.078 2.11 0.019 0.400
Residuals 77 2.86 0.037 0.708 0.162
Total 89 4.05 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.043 0.0214 1.03 0.039 0.833
Days 1 0.102 0.1019 4.92 0.092 0.023 *
seqRun 3 0.212 0.0706 3.41 0.191 0.575
Age 1 0.032 0.0317 1.53 0.029 0.856
Parity 1 0.043 0.0428 2.07 0.039 0.256
BMI 1 0.026 0.0261 1.26 0.024 0.713
AG15 1 0.008 0.0083 0.40 0.008 0.822
Residuals 31 0.642 0.0207 0.580 0.381
Total 41 1.107 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.9.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.285 0.1427 3.33 0.112 0.322
Days 1 0.070 0.0700 1.64 0.027 0.107
seqRun 3 0.144 0.0479 1.12 0.056 0.959
Age 1 0.312 0.3125 7.30 0.123 0.094 .
Parity 1 0.028 0.0277 0.65 0.011 0.929
BMI 1 0.018 0.0180 0.42 0.007 0.894
AG15 1 0.108 0.1078 2.52 0.042 0.834
Residuals 37 1.583 0.0428 0.621 0.873
Total 47 2.548 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.2 Differential abundance analysis Order taxonomic level
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 1 1 0 0 0 1 0 0 0 0
NotSig 25 25 26 25 10 25 24 4 26 10
Up 0 0 0 1 16 0 2 22 0 16
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 1 0
NotSig 26 25 26
Up 0 0 0Differentially abundant orders between T1D and non-T1D women were found. Significant differences between trimesters were also detected, however not all of the differentially abundant orders had a prevalence > 50% in one of the groups being compared or not all of them had LogFC > 0.5 or < -0.5.
Results for contrasts with significant differentially abundant orders shown below
9.2.1 Across all trimesters (T1D vs non-T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Enterobacteriales -0.953 0.00117 0.0305 0.146 97.9
2 Enterobacteriales -0.953 0.00117 0.0305 1.186 100.0[1] 329.2.2 Only Trimester 1 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Enterobacteriales -1.6 2.09e-05 0.000543 0.094 100
2 Enterobacteriales -1.6 2.09e-05 0.000543 1.811 1009.2.3 Only Trimester 2 (nonT1D vs T1D)
[1] "No DA taxa found"9.2.4 Only Trimester 3 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Bifidobacteriales 1.57 9.12e-05 0.00237 4.058 100
2 Bifidobacteriales 1.57 9.12e-05 0.00237 0.674 100
9.2.5 T1 vs T2 (All data)
[1] Classification LogFC P.Val adj.P.Val T1:mean%
[6] T1Prev% T2:mean% T2Prev% T3:mean% T3Prev%
<0 rows> (or 0-length row.names)9.2.6 T2 vs T3 (All data)
[1] Classification LogFC P.Val adj.P.Val mean%
[6] Prev%
<0 rows> (or 0-length row.names)9.2.7 T1 vs T3 (All data)
[1] Classification LogFC P.Val adj.P.Val T1:mean%
[6] T1Prev% T2:mean% T2Prev% T3:mean% T3Prev%
<0 rows> (or 0-length row.names)9.2.8 T1 vs T2 (in women with T1D)
Classification LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
2 Lactobacillales 0.555 0.013784 0.01792 0.192 91.7 0.244 95
4 Erysipelotrichales 0.589 0.001529 0.00234 0.093 100.0 0.082 100
7 Pasteurellales 0.645 0.000190 0.00162 0.224 66.7 0.047 80
3 Clostridiales 0.655 0.007688 0.01052 31.128 100.0 24.422 100
1 Coriobacteriales 0.677 0.021438 0.02534 1.206 100.0 1.036 100
8 Verrucomicrobiales 0.802 0.002682 0.00387 3.384 100.0 1.331 100
5 Selenomonadales 0.810 0.000704 0.00177 0.616 75.0 0.378 90
6 Enterobacteriales 0.862 0.000250 0.00162 1.811 100.0 0.963 1009.2.9 T2 vs T3 (in women with T1D)
Classification LogFC P.Val adj.P.Val T2:mean% T2Prev% T3:mean% T3Prev%
1 Lactobacillales -0.54 0.00683 0.177 0.244 95 0.404 1009.2.10 T1 vs T3 (in women with T1D)
Classification LogFC P.Val adj.P.Val T1:mean% T1Prev% T3:mean% T3Prev%
3 Pasteurellales 0.506 0.003865 0.02512 0.224 66.7 0.052 43.8
1 Bifidobacteriales 0.572 0.041568 0.06004 1.593 91.7 0.674 100.0
2 Enterobacteriales 0.627 0.008818 0.03928 1.811 100.0 0.996 100.0
4 Verrucomicrobiales 1.000 0.000274 0.00356 3.384 100.0 1.031 100.09.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa found"9.2.12 T2 vs T3 (in women without T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Bifidobacteriales -0.863 0.000306 0.00795 2.29 95
2 Bifidobacteriales -0.863 0.000306 0.00795 3.84 1009.2.13 T1 vs T3 (in women without T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Bifidobacteriales -0.877 0.00205 0.0534 1.88 100
2 Bifidobacteriales -0.877 0.00205 0.0534 3.84 10010 Phylum taxonomic level
10.1 Microbial community composition analysis at Phylum level (Beta diversity analysis)
10.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.36 0.119 3.37 0.092 0.695
Days 1 0.01 0.005 0.15 0.001 0.844
T1D_Time_Interaction 1 0.32 0.322 9.11 0.083 0.042 *
Age 1 0.04 0.040 1.14 0.010 0.431
Parity 1 0.06 0.057 1.62 0.015 0.635
BMI 1 0.05 0.054 1.52 0.014 0.847
HLA 2 0.05 0.025 0.70 0.013 0.846
T1Dstatus 1 0.03 0.029 0.82 0.007 0.610
Residuals 84 2.97 0.035 0.765 0.679
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.04210.1.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.117 0.0390 1.08 0.120 0.349
Nulliparous 1 0.236 0.2357 6.56 0.243 0.006 **
Age_LMP 1 0.015 0.0149 0.42 0.015 0.654
BMI_conception 1 0.010 0.0096 0.27 0.010 0.813
HLA.6DRML 2 0.052 0.0261 0.73 0.054 0.549
T1Dstatus 1 0.075 0.0749 2.08 0.077 0.141
Residuals 13 0.467 0.0359 0.481
Total 22 0.971 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.141Beta diversity Plot
10.1.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.174 0.0580 1.312 0.132 0.28
Nulliparous 1 0.012 0.0121 0.275 0.009 0.74
Age_LMP 1 0.021 0.0214 0.484 0.016 0.58
BMI_conception 1 0.069 0.0686 1.553 0.052 0.22
HLA.6DRML 2 0.008 0.0038 0.086 0.006 0.99
T1Dstatus 1 0.062 0.0619 1.401 0.047 0.24
Residuals 22 0.972 0.0442 0.738
Total 31 1.318 1.000 [1] 0.236Beta diversity Plot
10.1.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.094 0.0314 0.92 0.079 0.464
Nulliparous 1 0.036 0.0358 1.05 0.030 0.317
Age_LMP 1 0.030 0.0300 0.88 0.025 0.364
BMI_conception 1 0.117 0.1170 3.44 0.098 0.056 .
HLA.6DRML 2 0.016 0.0081 0.24 0.014 0.907
T1Dstatus 1 0.147 0.1466 4.31 0.123 0.031 *
Residuals 22 0.749 0.0340 0.630
Total 31 1.189 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.031Beta diversity Plot
10.1.5 Days within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.061 0.0307 1.58 0.052 0.57
seqRun 3 0.244 0.0812 4.19 0.206 0.53
Age 1 0.041 0.0414 2.13 0.035 0.77
Parity 1 0.051 0.0505 2.60 0.043 0.38
BMI 1 0.022 0.0217 1.12 0.018 0.66
Days 1 0.025 0.0246 1.27 0.021 0.26
Residuals 38 0.737 0.0194 0.624 0.75
Total 47 1.180 1.000 Beta diversity Plot
10.1.6 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.061 0.0307 1.60 0.052 0.59
seqRun 3 0.244 0.0812 4.23 0.206 0.50
Age 1 0.041 0.0414 2.16 0.035 0.76
Parity 1 0.051 0.0505 2.63 0.043 0.39
BMI 1 0.022 0.0217 1.13 0.018 0.70
Tri 2 0.051 0.0255 1.33 0.043 0.22
Residuals 37 0.710 0.0192 0.602 0.64
Total 47 1.180 1.000 Beta diversity Plot
10.1.7 Days within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.259 0.1297 3.09 0.108 0.324
seqRun 3 0.144 0.0480 1.15 0.060 0.942
Age 1 0.310 0.3097 7.38 0.129 0.073 .
Parity 1 0.015 0.0147 0.35 0.006 0.984
BMI 1 0.011 0.0109 0.26 0.005 0.768
Days 1 0.060 0.0599 1.43 0.025 0.128
Residuals 38 1.593 0.0419 0.666 0.491
Total 47 2.392 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
10.1.8 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.259 0.1297 2.99 0.108 0.337
seqRun 3 0.144 0.0480 1.11 0.060 0.926
Age 1 0.310 0.3097 7.14 0.129 0.081 .
Parity 1 0.015 0.0147 0.34 0.006 0.983
BMI 1 0.011 0.0109 0.25 0.005 0.797
Tri 2 0.048 0.0241 0.56 0.020 0.477
Residuals 37 1.605 0.0434 0.671 0.589
Total 47 2.392 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
10.1.9 Other factors
10.1.9.1 Age at conception
10.1.9.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.90 0.017 0.799
T1Dstatus 1 0.29 0.2942 8.13 0.076 0.058 .
seqRun 3 0.31 0.1039 2.87 0.080 0.590
Tri 2 0.04 0.0182 0.50 0.009 0.582
Age 1 0.04 0.0376 1.04 0.010 0.346
Parity 1 0.05 0.0547 1.51 0.014 0.591
BMI 1 0.05 0.0462 1.28 0.012 0.884
Age_Time_Interaction 1 0.03 0.0317 0.88 0.008 0.314
Residuals 83 3.00 0.0362 0.774 0.443
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.89 0.017 0.818
T1Dstatus 1 0.29 0.2942 8.06 0.076 0.055 .
seqRun 3 0.31 0.1039 2.85 0.080 0.588
Tri 2 0.04 0.0182 0.50 0.009 0.587
Age 1 0.04 0.0376 1.03 0.010 0.338
Parity 1 0.05 0.0547 1.50 0.014 0.606
BMI 1 0.05 0.0462 1.26 0.012 0.893
Age_Time_Interaction 1 0.00 0.0045 0.12 0.001 0.846
Residuals 83 3.03 0.0365 0.781 0.534
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.91 0.017 0.809
T1Dstatus 1 0.29 0.2942 8.20 0.076 0.056 .
seqRun 3 0.31 0.1039 2.90 0.080 0.598
Tri 2 0.04 0.0182 0.51 0.009 0.588
Age 1 0.04 0.0376 1.05 0.010 0.349
Parity 1 0.05 0.0547 1.52 0.014 0.593
BMI 1 0.05 0.0462 1.29 0.012 0.892
Age_Time_Interaction 1 0.06 0.0550 1.53 0.014 0.142
Residuals 83 2.98 0.0359 0.768 0.437
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.1.4 Age at conception (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.90 0.017 0.795
T1Dstatus 1 0.29 0.2942 8.15 0.076 0.058 .
seqRun 3 0.31 0.1039 2.88 0.080 0.609
Tri 2 0.04 0.0182 0.50 0.009 0.596
Parity 1 0.06 0.0577 1.60 0.015 0.487
BMI 1 0.04 0.0388 1.07 0.010 0.880
Age 1 0.04 0.0419 1.16 0.011 0.509
Residuals 84 3.03 0.0361 0.782 0.477
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.2 Body max index (BMI)
10.1.9.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.90 0.017 0.803
T1Dstatus 1 0.29 0.2942 8.11 0.076 0.051 .
seqRun 3 0.31 0.1039 2.86 0.080 0.588
Tri 2 0.04 0.0182 0.50 0.009 0.585
Age 1 0.04 0.0376 1.04 0.010 0.339
Parity 1 0.05 0.0547 1.51 0.014 0.587
BMI 1 0.05 0.0462 1.27 0.012 0.892
BMI_Time_Interaction 1 0.02 0.0219 0.60 0.006 0.404
Residuals 83 3.01 0.0363 0.776 0.450
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.89 0.017 0.770
T1Dstatus 1 0.29 0.2942 8.06 0.076 0.071 .
seqRun 3 0.31 0.1039 2.85 0.080 0.594
Tri 2 0.04 0.0182 0.50 0.009 0.606
Age 1 0.04 0.0376 1.03 0.010 0.337
Parity 1 0.05 0.0547 1.50 0.014 0.559
BMI 1 0.05 0.0462 1.26 0.012 0.895
BMI_Time_Interaction 1 0.00 0.0037 0.10 0.001 0.819
Residuals 83 3.03 0.0365 0.781 0.506
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.2.3 BMI interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.90 0.017 0.820
T1Dstatus 1 0.29 0.2942 8.09 0.076 0.044 *
seqRun 3 0.31 0.1039 2.86 0.080 0.607
Tri 2 0.04 0.0182 0.50 0.009 0.547
Age 1 0.04 0.0376 1.03 0.010 0.336
Parity 1 0.05 0.0547 1.51 0.014 0.623
BMI 1 0.05 0.0462 1.27 0.012 0.893
BMI_Time_Interaction 1 0.02 0.0173 0.48 0.004 0.359
Residuals 83 3.02 0.0363 0.778 0.452
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.2.4 BMI (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.90 0.017 0.802
T1Dstatus 1 0.29 0.2942 8.15 0.076 0.051 .
seqRun 3 0.31 0.1039 2.88 0.080 0.605
Tri 2 0.04 0.0182 0.50 0.009 0.601
Age 1 0.04 0.0376 1.04 0.010 0.330
Parity 1 0.05 0.0547 1.51 0.014 0.587
BMI 1 0.05 0.0462 1.28 0.012 0.897
Residuals 84 3.03 0.0361 0.782 0.468
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.3 HLA type
10.1.9.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.90 0.017 0.806
T1Dstatus 1 0.29 0.2942 8.09 0.076 0.059 .
Days 1 0.01 0.0052 0.14 0.001 0.877
seqRun 3 0.31 0.1031 2.84 0.080 0.601
Age 1 0.04 0.0363 1.00 0.009 0.350
Parity 1 0.05 0.0542 1.49 0.014 0.587
BMI 1 0.05 0.0521 1.43 0.013 0.867
HLA_Time_Interaction 1 0.01 0.0096 0.27 0.002 0.350
Residuals 84 3.05 0.0364 0.787 0.464
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.90 0.017 0.825
T1Dstatus 1 0.29 0.2942 8.09 0.076 0.041 *
Days 1 0.01 0.0052 0.14 0.001 0.841
seqRun 3 0.31 0.1031 2.84 0.080 0.586
Age 1 0.04 0.0363 1.00 0.009 0.359
Parity 1 0.05 0.0542 1.49 0.014 0.592
BMI 1 0.05 0.0521 1.43 0.013 0.862
HLA_Time_Interaction 1 0.01 0.0105 0.29 0.003 0.879
Residuals 84 3.05 0.0363 0.787 0.518
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.89 0.017 0.81
T1Dstatus 1 0.29 0.2942 8.07 0.076 0.04 *
Days 1 0.01 0.0052 0.14 0.001 0.84
seqRun 3 0.31 0.1031 2.83 0.080 0.58
Age 1 0.04 0.0363 1.00 0.009 0.36
Parity 1 0.05 0.0542 1.49 0.014 0.61
BMI 1 0.05 0.0521 1.43 0.013 0.90
HLA_Time_Interaction 1 0.00 0.0021 0.06 0.001 0.97
Residuals 84 3.06 0.0364 0.789 0.47
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.01 0.0111 0.31 0.003 0.66
seqRun 3 0.35 0.1170 3.25 0.090 0.59
Age 1 0.03 0.0300 0.83 0.008 0.64
Parity 1 0.06 0.0561 1.56 0.014 0.39
BMI 1 0.12 0.1160 3.22 0.030 0.31
T1Dstatus 1 0.20 0.2028 5.63 0.052 0.11
HLA 2 0.05 0.0247 0.69 0.013 0.85
Residuals 85 3.06 0.0360 0.790 0.42
Total 95 3.88 1.000 10.1.9.4 Parity
10.1.9.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.92 0.017 0.822
T1Dstatus 1 0.29 0.2942 8.26 0.076 0.049 *
Days 1 0.01 0.0052 0.14 0.001 0.859
seqRun 3 0.31 0.1031 2.89 0.080 0.588
Age 1 0.04 0.0363 1.02 0.009 0.347
Parity 1 0.05 0.0542 1.52 0.014 0.625
BMI 1 0.05 0.0521 1.46 0.013 0.870
Parity_Time_Interaction 1 0.07 0.0714 2.00 0.018 0.046 *
Residuals 84 2.99 0.0356 0.771 0.342
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.4.2 Parity (no interaction but within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.055 0.0276 0.66 0.057 0.62
T1Dstatus 1 0.012 0.0121 0.29 0.012 0.82
seqRun 1 0.080 0.0796 1.89 0.082 0.05 *
Age 1 0.030 0.0298 0.71 0.031 0.72
BMI 1 0.020 0.0200 0.48 0.021 0.79
Parity 1 0.143 0.1434 3.41 0.148 0.43
Residuals 15 0.631 0.0421 0.650 0.72
Total 22 0.971 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.4.3 Parity (no interaction but within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.020 0.0099 0.24 0.012 0.95
T1Dstatus 1 0.212 0.2121 5.23 0.131 0.03 *
seqRun 1 0.046 0.0456 1.12 0.028 0.92
Age 1 0.013 0.0133 0.33 0.008 0.23
BMI 1 0.019 0.0185 0.46 0.011 0.45
Parity 1 0.013 0.0133 0.33 0.008 0.83
Residuals 32 1.299 0.0406 0.801 0.53
Total 39 1.621 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.4.4 Parity (no interaction but within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.033 0.0167 0.46 0.026 0.775
T1Dstatus 1 0.184 0.1840 5.12 0.146 0.017 *
seqRun 1 0.012 0.0124 0.35 0.010 0.860
Age 1 0.024 0.0241 0.67 0.019 0.716
BMI 1 0.037 0.0368 1.02 0.029 0.771
Parity 1 0.072 0.0716 1.99 0.057 0.782
Residuals 25 0.899 0.0360 0.713 0.314
Total 32 1.261 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.5 Mode of delivery
10.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.93 0.017 0.785
T1Dstatus 1 0.29 0.2942 8.35 0.076 0.055 .
MOD 2 0.11 0.0547 1.55 0.028 0.625
Days 1 0.00 0.0042 0.12 0.001 0.864
seqRun 3 0.27 0.0910 2.58 0.070 0.640
Age 1 0.09 0.0852 2.42 0.022 0.070 .
Parity 1 0.05 0.0528 1.50 0.014 0.566
BMI 1 0.08 0.0779 2.21 0.020 0.638
MOD_Time_Interaction 1 0.03 0.0293 0.83 0.008 0.734
Residuals 82 2.89 0.0352 0.745 0.553
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.92 0.017 0.791
T1Dstatus 1 0.29 0.2942 8.30 0.076 0.050 *
MOD 2 0.11 0.0547 1.54 0.028 0.603
Days 1 0.00 0.0042 0.12 0.001 0.882
seqRun 3 0.27 0.0910 2.57 0.070 0.619
Age 1 0.09 0.0852 2.40 0.022 0.086 .
Parity 1 0.05 0.0528 1.49 0.014 0.593
BMI 1 0.08 0.0779 2.20 0.020 0.639
MOD_Time_Interaction 1 0.01 0.0098 0.27 0.003 0.973
Residuals 82 2.91 0.0355 0.750 0.720
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.92 0.017 0.822
T1Dstatus 1 0.29 0.2942 8.34 0.076 0.045 *
MOD 2 0.11 0.0547 1.55 0.028 0.597
Days 1 0.00 0.0042 0.12 0.001 0.870
seqRun 3 0.27 0.0910 2.58 0.070 0.639
Age 1 0.09 0.0852 2.41 0.022 0.066 .
Parity 1 0.05 0.0528 1.50 0.014 0.611
BMI 1 0.08 0.0779 2.21 0.020 0.637
MOD_Time_Interaction 1 0.02 0.0244 0.69 0.006 0.940
Residuals 82 2.89 0.0353 0.746 0.707
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.01 0.0111 0.31 0.003 0.697
seqRun 3 0.35 0.1170 3.33 0.090 0.554
Age 1 0.03 0.0300 0.85 0.008 0.614
Parity 1 0.06 0.0561 1.60 0.014 0.395
BMI 1 0.12 0.1160 3.30 0.030 0.328
HLA 2 0.03 0.0153 0.43 0.008 0.956
T1Dstatus 1 0.22 0.2217 6.30 0.057 0.084 .
MOD 2 0.15 0.0727 2.07 0.037 0.418
Residuals 83 2.92 0.0352 0.752 0.504
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.6 Carbohydrate intake
10.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.97 0.017 0.766
T1Dstatus 1 0.29 0.2942 8.72 0.076 0.052 .
Carbs 1 0.03 0.0320 0.95 0.008 0.644
seqRun 3 0.37 0.1230 3.65 0.095 0.314
Tri 2 0.03 0.0160 0.48 0.008 0.650
Age 1 0.09 0.0914 2.71 0.024 0.053 .
Parity 1 0.07 0.0670 1.99 0.017 0.237
BMI 1 0.09 0.0900 2.67 0.023 0.567
Carb_Time_Interaction 1 0.07 0.0736 2.18 0.019 0.440
Residuals 82 2.77 0.0337 0.713 0.252
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.95 0.017 0.780
T1Dstatus 1 0.29 0.2942 8.56 0.076 0.068 .
Carbs 1 0.03 0.0320 0.93 0.008 0.623
seqRun 3 0.37 0.1230 3.58 0.095 0.329
Tri 2 0.03 0.0160 0.47 0.008 0.614
Age 1 0.09 0.0914 2.66 0.024 0.053 .
Parity 1 0.07 0.0670 1.95 0.017 0.234
BMI 1 0.09 0.0900 2.62 0.023 0.556
Carb_Time_Interaction 1 0.02 0.0199 0.58 0.005 0.921
Residuals 82 2.82 0.0344 0.727 0.432
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.95 0.017 0.790
T1Dstatus 1 0.29 0.2942 8.62 0.076 0.062 .
Carbs 1 0.03 0.0320 0.94 0.008 0.632
seqRun 3 0.37 0.1230 3.60 0.095 0.323
Tri 2 0.03 0.0160 0.47 0.008 0.641
Age 1 0.09 0.0914 2.68 0.024 0.044 *
Parity 1 0.07 0.0670 1.96 0.017 0.201
BMI 1 0.09 0.0900 2.64 0.023 0.560
Carb_Time_Interaction 1 0.04 0.0392 1.15 0.010 0.699
Residuals 82 2.80 0.0341 0.722 0.326
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.6.4 Carbohydrate (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.36 0.1190 3.48 0.092 0.001 ***
Tri 2 0.03 0.0171 0.50 0.009 0.635
Age 1 0.03 0.0309 0.90 0.008 0.586
Parity 1 0.06 0.0552 1.62 0.014 0.676
BMI 1 0.11 0.1056 3.09 0.027 0.547
HLA 2 0.03 0.0140 0.41 0.007 0.941
T1Dstatus 1 0.24 0.2351 6.87 0.061 0.056 .
Carbs 1 0.19 0.1948 5.69 0.050 0.092 .
Residuals 83 2.84 0.0342 0.732 0.244
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.7 Fibre intake
10.1.9.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.90 0.017 0.799
T1Dstatus 1 0.29 0.2942 8.16 0.076 0.058 .
Fiber 1 0.00 0.0031 0.09 0.001 0.977
seqRun 3 0.32 0.1075 2.98 0.083 0.511
Tri 2 0.04 0.0181 0.50 0.009 0.595
Age 1 0.06 0.0559 1.55 0.014 0.174
Parity 1 0.06 0.0621 1.72 0.016 0.332
BMI 1 0.06 0.0597 1.66 0.015 0.763
Fiber_Time_Interaction 1 0.03 0.0254 0.70 0.007 0.472
Residuals 82 2.96 0.0360 0.762 0.573
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.90 0.017 0.812
T1Dstatus 1 0.29 0.2942 8.10 0.076 0.052 .
Fiber 1 0.00 0.0031 0.09 0.001 0.977
seqRun 3 0.32 0.1075 2.96 0.083 0.509
Tri 2 0.04 0.0181 0.50 0.009 0.607
Age 1 0.06 0.0559 1.54 0.014 0.166
Parity 1 0.06 0.0621 1.71 0.016 0.334
BMI 1 0.06 0.0597 1.64 0.015 0.758
Fiber_Time_Interaction 1 0.00 0.0044 0.12 0.001 0.947
Residuals 82 2.98 0.0363 0.767 0.631
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0326 0.90 0.017 0.788
T1Dstatus 1 0.29 0.2942 8.14 0.076 0.055 .
Fiber 1 0.00 0.0031 0.09 0.001 0.979
seqRun 3 0.32 0.1075 2.97 0.083 0.509
Tri 2 0.04 0.0181 0.50 0.009 0.558
Age 1 0.06 0.0559 1.55 0.014 0.162
Parity 1 0.06 0.0621 1.72 0.016 0.339
BMI 1 0.06 0.0597 1.65 0.015 0.760
Fiber_Time_Interaction 1 0.02 0.0175 0.48 0.005 0.561
Residuals 82 2.96 0.0361 0.764 0.571
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.7.4 Fibre (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.36 0.1190 3.31 0.092 0.672
Tri 2 0.03 0.0171 0.48 0.009 0.617
Age 1 0.03 0.0309 0.86 0.008 0.568
Parity 1 0.06 0.0552 1.54 0.014 0.692
BMI 1 0.11 0.1056 2.94 0.027 0.551
HLA 2 0.03 0.0140 0.39 0.007 0.964
T1Dstatus 1 0.24 0.2351 6.54 0.061 0.094 .
Fiber 1 0.05 0.0529 1.47 0.014 0.472
Residuals 83 2.98 0.0359 0.768 0.531
Total 95 3.88 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.8 1,5-AG (glucose control measurement)
10.1.9.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.11 0.054 1.56 0.029 0.627
T1Dstatus 1 0.35 0.351 10.14 0.093 0.032 *
Days 1 0.00 0.000 -0.01 0.000 0.987
seqRun 3 0.25 0.084 2.44 0.067 0.792
Age 1 0.06 0.056 1.63 0.015 0.287
Parity 1 0.05 0.052 1.50 0.014 0.509
BMI 1 0.03 0.027 0.78 0.007 0.930
AG15 1 0.18 0.181 5.24 0.048 0.001 ***
AG15_T1D_Interaction 1 0.07 0.068 1.97 0.018 0.462
Residuals 77 2.66 0.035 0.708 0.151
Total 89 3.76 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.039 0.0195 1.03 0.039 0.732
Days 1 0.092 0.0922 4.87 0.093 0.022 *
seqRun 3 0.189 0.0629 3.33 0.191 0.613
Age 1 0.009 0.0088 0.47 0.009 0.979
Parity 1 0.051 0.0512 2.71 0.052 0.345
BMI 1 0.020 0.0200 1.06 0.020 0.772
AG15 1 0.005 0.0047 0.25 0.005 0.655
Residuals 31 0.586 0.0189 0.592 0.440
Total 41 0.991 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.1.9.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.259 0.1297 3.23 0.108 0.33
Days 1 0.070 0.0696 1.73 0.029 0.14
seqRun 3 0.140 0.0468 1.16 0.059 0.95
Age 1 0.304 0.3040 7.56 0.127 0.09 .
Parity 1 0.014 0.0144 0.36 0.006 0.98
BMI 1 0.011 0.0109 0.27 0.005 0.79
AG15 1 0.106 0.1063 2.64 0.044 0.81
Residuals 37 1.487 0.0402 0.622 0.87
Total 47 2.392 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 110.2 Differential abundance analysis Phylum taxonomic level
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 0 0 0 0 0 0 0 0 0 0
NotSig 8 8 7 8 8 8 8 8 8 8
Up 0 0 1 0 0 0 0 0 0 0
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 0 1
NotSig 8 8 7
Up 0 0 0One differentially abundant phylum was detected between T1 and T3 only in non-T1D women.
Results for contrasts with significant differentially abundant phyla shown below
10.2.1 Across all trimesters (T1D vs non-T1D)
[1] "No DA taxa found"10.2.2 Only Trimester 1 (nonT1D vs T1D)
[1] "No DA taxa found"10.2.3 Only Trimester 2 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 Firmicutes 0.842 0.0175 0.0699 36.3 100 26.8 10010.2.4 Only Trimester 3 (nonT1D vs T1D)
[1] "No DA taxa found"The abundance of the Phylum Firmicutes is decreased in T1D women in comparison to non-T1D women, however, this difference is borderline significant (P=0.07).
10.2.5 T1 vs T2 (All data)
[1] "No DA taxa found"10.2.6 T2 vs T3 (All data)
[1] "No DA taxa"10.2.7 T1 vs T3 (All data)
[1] "No DA taxa found"10.2.8 T1 vs T2 (in women with T1D)
[1] "No DA taxa found"10.2.9 T2 vs T3 (in women with T1D)
[1] "No DA taxa found"10.2.10 T1 vs T3 (in women with T1D)
[1] "No DA taxa found"10.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa found"10.2.12 T2 vs T3 (in women without T1D)
[1] "No DA taxa found"10.2.13 T1 vs T3 (in women without T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Actinobacteria -1.17 0.00368 0.0294 2.73 100
2 Actinobacteria -1.17 0.00368 0.0294 5.64 100
10.3 Firmicutes/Bacteroides ratio (phylum taxonomic level analysis)
11 Functional analysis (Pathways)
In order to functionally annotate the metagenomic data, we used Kraken2 to filter out human genes more stringently before running HUMAnN2 again. For each sample, the HUMAnN2 output contained the following files:
XX_pathcoverage.tsv: This file details the abundance of each pathway in the community as a function of the abundances of the pathway’s component reactions, with each reaction’s abundance computed as the sum over abundances of genes catalyzing the reaction. Pathways with zero abundance are not included in the file. Pathway abundance is proportional to the number of complete “copies” of the pathway in the community (from the HUMAnN2 manual).
XX_genefamilies.tsv: This file details the abundance of each gene family in the community. Gene families are groups of evolutionarily-related protein-coding sequences that often perform similar functions. Gene family abundance at the community level is stratified to show the contributions from known and unknown species. Individual species’ abundance contributions sum to the community total abundance (from the HUMAnN2 manual).
- The genefamilies.csv file can contain a very large number of features depending on the complexity of your underlying sample. In order to simplify the exploration of gene family abundance data, users can regroup gene families into other functional categories (from the HUMAnN2 manual). Therefore, we regrouped our resulting gene families into MetaCyc reactions and Kegg Orthology (KO) functional categories, which has to be done in a per sample manner. Example:
- humann2_regroup_table –input NGU5366A1_genefamilies.tsv –groups uniref90_ko –output ./NGU5366A1_genefamilies_Regrouped_KO.tsv
- HUMAnN2 quantifies genes and pathways in units of RPKs (reads per kilobase). These account for gene length but not sample sequencing depth. Therefore, a user will renormalize their samples prior to downstream analysis to relative abundance or copies per million (CPM) units. Both of these represent “total sum scaling (TSS)”-style normalization: in the former case, each sample is constrained to sum to 1, whereas in the latter case (CPMs) samples are constrained to sum to 1 million. Units out of 1 million are often more convenient for tables with many, many features (such as genefamilies.tsv tables). CPM as used here does not refer to unnormalized COUNTS per million, but rather copies per million. CPMs as used here are a generic analog of the TPM (transcript per million) unit in RNA-seq. You may wish to use the abbreviation CoPM for added clarity. (from the HUMAnN2 manual). We normilized the counts for each sample file for their three functional tables (XX_genefamilies.tsv, XX_genefamilies_Regrouped_KO.tsv and XX_genefamilies_Regrouped_MetaCyc.tsv) to CoPM. Example:
- humann2_renorm_table –input NGU5366A1_genefamilies_Regrouped_KO.tsv –output NGU5366A1_genefamilies_Regrouped_KO_CoPM.tsv –units cpm
- Each normalized file, contained one sample. Therefore, in order to obtain a table with the functional profiles for all the samples, we need to join them into one. Example:
- humann2_join_tables –input KO –output Pregnancy_genefamilies_KO_Rel.tsv –file_name Complete_genefamilies_Regrouped_KO_Rel.tsv
- The functional profiles are stratified, which means that the sum of the species abundance of a given gene gives the abundance of the gene at the community level. The stratification shows the contributions from known and unknown species to a given function. If we are interested in knowing if there is a significant difference in the abundance of a specific function at the community level (i.e. irrespective of which species is contributing to it), the abundances need to be unstratified prior to the analysis. This is done as in the following exmaple:
- humann2_split_stratified_table –input Complete_genefamilies_Regrouped_KO_Rel.tsv –output Split/
The folder split will contain stratified and unstratified abundances.
Note: Scripts used for regrouping, normalization, joinning tables and stratification are part of HUMAnN2.
The resulting files for pathways, metacyc reactions and Kegg orthology (KO) gene categories were imported into R to process with the Phyloseq (https://github.com/joey711/phyloseq) and other packages. The analysis performed in R is described in this document.
11.1 Bar plots taxonomy
11.2 Functional Alpha diversity (Days)
Call:
geeglm(formula = Observed ~ t1dfactor * days_c + age_c + nullip +
bmi_c + HLA + SeqRun, data = DivCal_R_df, id = motherid,
corstr = "exchangeable")
Coefficients:
Estimate Std.err Wald Pr(>|W|)
(Intercept) 266.1375 9.5075 783.58 <2e-16 ***
t1dfactorT1D 8.6538 7.2846 1.41 0.235
days_c 0.0825 0.0685 1.45 0.229
age_c 0.5975 1.0111 0.35 0.555
nullipYes -17.8705 7.3682 5.88 0.015 *
bmi_c 0.7354 0.7872 0.87 0.350
HLADRXX 7.7104 9.6243 0.64 0.423
HLAGroup3o4 8.5421 9.4042 0.83 0.364
SeqRun3 9.9935 9.5574 1.09 0.296
SeqRun4 17.7622 9.8253 3.27 0.071 .
SeqRun6 1.5268 11.5111 0.02 0.894
t1dfactorT1D:days_c -0.0703 0.1093 0.41 0.520
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Estimated Scale Parameters:
Estimate Std.err
(Intercept) 1023 150
Correlation: Structure = exchangeable Link = identity
Estimated Correlation Parameters:
Estimate Std.err
alpha 0.0932 0.164
Number of clusters: 83 Maximum cluster size: 3 No significant differences between T1D and non-T1D alpha diversity were detected.
11.3 Functional Alpha diversity (Trimesters)
Call:
geeglm(formula = Observed ~ t1dfactor * Tri + age_c + nullip +
bmi_c + HLA + SeqRun, data = DivCal_R_df, id = motherid,
corstr = "exchangeable")
Coefficients:
Estimate Std.err Wald Pr(>|W|)
(Intercept) 257.004 12.251 440.09 <2e-16 ***
t1dfactorT1D 18.750 15.345 1.49 0.222
TriT2 9.800 10.021 0.96 0.328
TriT3 15.835 12.188 1.69 0.194
age_c 0.713 1.002 0.51 0.477
nullipYes -18.025 7.356 6.00 0.014 *
bmi_c 0.692 0.820 0.71 0.399
HLADRXX 8.016 9.847 0.66 0.416
HLAGroup3o4 9.067 9.506 0.91 0.340
SeqRun3 8.962 9.739 0.85 0.357
SeqRun4 17.343 9.859 3.09 0.079 .
SeqRun6 0.470 11.539 0.00 0.968
t1dfactorT1D:TriT2 -11.512 17.483 0.43 0.510
t1dfactorT1D:TriT3 -15.144 18.593 0.66 0.415
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Estimated Scale Parameters:
Estimate Std.err
(Intercept) 1022 147
Correlation: Structure = exchangeable Link = identity
Estimated Correlation Parameters:
Estimate Std.err
alpha 0.104 0.173
Number of clusters: 83 Maximum cluster size: 3 11.4 Beta diversity analysis
11.4.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.088 0.0293 1.66 0.046 0.001 ***
Days 1 0.015 0.0153 0.87 0.008 0.149
T1D_Time_Interaction 1 0.072 0.0719 4.07 0.037 0.101
Age 1 0.054 0.0544 3.08 0.028 0.994
Parity 1 0.066 0.0658 3.72 0.034 0.115
BMI 1 0.022 0.0222 1.26 0.012 0.979
HLA 2 0.090 0.0452 2.56 0.047 0.395
T1Dstatus 1 0.027 0.0274 1.55 0.014 0.789
Residuals 84 1.484 0.0177 0.773 0.461
Total 95 1.919 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.10111.4.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.060 0.0201 0.853 0.113 0.635
Nulliparous 1 0.037 0.0370 1.570 0.069 0.134
Age_LMP 1 0.020 0.0203 0.862 0.038 0.522
BMI_conception 1 0.012 0.0123 0.520 0.023 0.859
HLA.6DRML 2 0.049 0.0244 1.035 0.092 0.390
T1Dstatus 1 0.048 0.0476 2.018 0.089 0.072 .
Residuals 13 0.306 0.0236 0.575
Total 22 0.533 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.072Beta diversity Plot
11.4.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.064 0.02125 1.125 0.107 0.34
Nulliparous 1 0.026 0.02553 1.352 0.043 0.21
Age_LMP 1 0.024 0.02350 1.244 0.039 0.26
BMI_conception 1 0.009 0.00856 0.453 0.014 0.94
HLA.6DRML 2 0.040 0.02004 1.061 0.067 0.38
T1Dstatus 1 0.020 0.02017 1.068 0.034 0.39
Residuals 22 0.416 0.01889 0.696
Total 31 0.597 1.000 [1] 0.386Beta diversity Plot
11.4.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.045 0.0148 0.758 0.070 0.847
Nulliparous 1 0.025 0.0248 1.266 0.039 0.197
Age_LMP 1 0.022 0.0215 1.098 0.034 0.328
BMI_conception 1 0.030 0.0305 1.557 0.048 0.096 .
HLA.6DRML 2 0.035 0.0174 0.886 0.055 0.617
T1Dstatus 1 0.046 0.0461 2.355 0.073 0.007 **
Residuals 22 0.431 0.0196 0.681
Total 31 0.633 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.007Beta diversity Plot
11.4.5 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.058 0.0288 1.54 0.054 0.88
seqRun 3 0.108 0.0359 1.91 0.100 0.62
Age 1 0.033 0.0332 1.77 0.031 0.87
Parity 1 0.117 0.1170 6.23 0.109 0.14
BMI 1 0.037 0.0370 1.97 0.034 0.39
Tri 2 0.029 0.0145 0.77 0.027 0.30
Residuals 37 0.695 0.0188 0.646 0.80
Total 47 1.076 1.000 Beta diversity Plot
11.4.6 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.075 0.0376 3.04 0.098 0.340
seqRun 3 0.077 0.0255 2.06 0.100 0.784
Age 1 0.082 0.0823 6.64 0.108 0.109
Parity 1 0.021 0.0211 1.70 0.028 0.949
BMI 1 0.030 0.0301 2.43 0.039 0.059 .
Tri 2 0.021 0.0103 0.83 0.027 0.348
Residuals 37 0.458 0.0124 0.600 0.254
Total 47 0.764 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
11.5 Differential abundance analysis
11.5.1 Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
11.5.1.1 Results from differential abundance analysis
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 0 0 0 3 0 0 0 0 0 0
NotSig 420 420 420 415 420 420 419 420 420 419
Up 0 0 0 2 0 0 1 0 0 1
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 2 0 0
NotSig 418 420 419
Up 0 0 1Results for contrasts with significant differentially abundant strains shown below
11.5.2 Across all trimesters (T1D vs non-T1D)
Classification LogFC P.Val
1 PWY-1269: CMP-3-deoxy-D-manno-octulosonate biosynthesis I -0.714 0.000232
2 PWY-6545: pyrimidine deoxyribonucleotides de novo biosynthesis III 0.493 0.000417
adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 0.0875 45.8 100 62.7 100
2 0.0875 38.7 100 31.5 10011.5.3 Only Trimester 1 (nonT1D vs T1D)
[1] "No DA taxa found"11.5.4 Only Trimester 2 (nonT1D vs T1D)
[1] "No DA taxa found"11.5.5 Only Trimester 3 (nonT1D vs T1D)
Function LogFC
2 HISDEG-PWY: L-histidine degradation I -0.933
3 PWY-1269: CMP-3-deoxy-D-manno-octulosonate biosynthesis I -0.910
5 PWY-5695: urate biosynthesis/inosine 5-phosphate degradation -0.590
6 PWY-6545: pyrimidine deoxyribonucleotides de novo biosynthesis III 0.539
1 BRANCHED-CHAIN-AA-SYN-PWY: superpathway of branched amino acid biosynthesis 0.716
8 PWY-7357: thiamin formation from pyrithiamine and oxythiamine (yeast) 0.795
4 PWY-5103: L-isoleucine biosynthesis III 0.808
7 PWY-7237: myo-, chiro- and scillo-inositol degradation 1.843
P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
2 1.49e-04 0.0168 0.476 100 0.706 100.0
3 8.19e-05 0.0168 0.421 100 0.653 100.0
5 2.68e-04 0.0225 0.992 100 1.379 100.0
6 1.07e-03 0.0560 0.402 100 0.312 100.0
1 1.60e-04 0.0168 1.243 100 0.804 100.0
8 7.18e-04 0.0503 0.604 100 0.379 100.0
4 1.12e-04 0.0168 1.120 100 0.683 100.0
7 1.04e-03 0.0560 0.067 100 0.020 93.811.5.6 T1 vs T2 (All data)
[1] "No DA taxa found"11.5.7 T2 vs T3 (All data)
[1] "No DA taxa"11.5.8 T1 vs T3 (All data)
Function LogFC P.Val adj.P.Val mean% Prev%
1 P122-PWY: heterolactic fermentation 1.92 5.97e-06 0.00251 0.019 82.6
2 P122-PWY: heterolactic fermentation 1.92 5.97e-06 0.00251 0.014 75.011.5.9 T1 vs T2 (in women with T1D)
[1] Function LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
<0 rows> (or 0-length row.names)11.5.10 T2 vs T3 (in women with T1D)
[1] Function LogFC P.Val adj.P.Val T2:mean% T2Prev% T3:mean% T3Prev%
<0 rows> (or 0-length row.names)11.5.11 T1 vs T3 (in women with T1D)
Function
3 PWY0-1277: 3-phenylpropanoate and 3-(3-hydroxyphenyl)propanoate degradation
1 HCAMHPDEG-PWY: 3-phenylpropanoate and 3-(3-hydroxyphenyl)propanoate degradation to 2-oxopent-4-enoate
2 PWY-6690: cinnamate and 3-hydroxycinnamate degradation to 2-oxopent-4-enoate
LogFC P.Val adj.P.Val T1:mean% T1Prev% T3:mean% T3Prev%
3 -1.36 0.00104 0.0731 0.005 25 0.011 56.2
1 -1.10 0.00147 0.0731 0.003 25 0.007 56.2
2 -1.10 0.00147 0.0731 0.003 25 0.007 56.211.5.12 T1 vs T2 (in women without T1D)
Function LogFC P.Val adj.P.Val
2 PWY-5918: superpathay of heme biosynthesis from glutamate -1.88 0.000185 0.0399
1 HEME-BIOSYNTHESIS-II: heme biosynthesis I (aerobic) -1.80 0.000190 0.0399
T1:mean% T1Prev% T2:mean% T2Prev%
2 0.002 18.2 0.008 75
1 0.002 27.3 0.006 9511.5.13 T2 vs T3 (in women without T1D)
[1] "No DA taxa found"11.5.14 T1 vs T3 (in women without T1D)
Function LogFC P.Val adj.P.Val mean% Prev%
T1 P122-PWY: heterolactic fermentation 2.66 9.58e-06 0.00402 0.024 90.9
T3 P122-PWY: heterolactic fermentation 2.66 9.58e-06 0.00402 0.008 41.2[1] 412 Functional analysis (Kegg Orthology)
12.1 Bar plots taxonomy
12.2 Functional Alpha diversity (Days)
12.3 Functional Alpha diversity (Trimesters)
Call:
geeglm(formula = Observed ~ t1dfactor * Tri + age_c + nullip +
bmi_c + HLA + SeqRun, data = DivCal_R_df, id = motherid,
corstr = "exchangeable")
Coefficients:
Estimate Std.err Wald Pr(>|W|)
(Intercept) 3150.13 176.13 319.89 <2e-16 ***
t1dfactorT1D 233.53 217.71 1.15 0.2834
TriT2 89.77 144.02 0.39 0.5331
TriT3 147.61 170.25 0.75 0.3859
age_c 6.66 13.88 0.23 0.6314
nullipYes -270.52 101.80 7.06 0.0079 **
bmi_c 3.21 11.13 0.08 0.7730
HLADRXX -10.47 136.48 0.01 0.9389
HLAGroup3o4 93.64 129.94 0.52 0.4711
SeqRun3 -2.79 127.87 0.00 0.9826
SeqRun4 118.31 128.05 0.85 0.3555
SeqRun6 -167.52 150.11 1.25 0.2644
t1dfactorT1D:TriT2 -116.05 244.44 0.23 0.6350
t1dfactorT1D:TriT3 -176.04 254.17 0.48 0.4885
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Estimated Scale Parameters:
Estimate Std.err
(Intercept) 195761 29111
Correlation: Structure = exchangeable Link = identity
Estimated Correlation Parameters:
Estimate Std.err
alpha 0.183 0.183
Number of clusters: 83 Maximum cluster size: 3 12.4 Beta diversity analysis
12.4.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.157 0.0524 2.10 0.057 0.001 ***
Days 1 0.025 0.0248 0.99 0.009 0.121
T1D_Time_Interaction 1 0.121 0.1207 4.83 0.044 0.044 *
Age 1 0.088 0.0880 3.52 0.032 0.993
Parity 1 0.070 0.0703 2.81 0.025 0.212
BMI 1 0.050 0.0503 2.01 0.018 0.982
HLA 2 0.133 0.0665 2.66 0.048 0.334
T1Dstatus 1 0.031 0.0307 1.23 0.011 0.940
Residuals 84 2.099 0.0250 0.757 0.428
Total 95 2.774 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.04412.4.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.082 0.0275 0.815 0.111 0.761
Nulliparous 1 0.038 0.0375 1.112 0.051 0.375
Age_LMP 1 0.040 0.0402 1.191 0.054 0.301
BMI_conception 1 0.026 0.0259 0.769 0.035 0.671
HLA.6DRML 2 0.063 0.0317 0.940 0.086 0.584
T1Dstatus 1 0.053 0.0528 1.565 0.071 0.098 .
Residuals 13 0.439 0.0337 0.592
Total 22 0.741 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.098Beta diversity Plot
12.4.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.096 0.0320 1.20 0.111 0.219
Nulliparous 1 0.042 0.0425 1.59 0.049 0.096 .
Age_LMP 1 0.035 0.0347 1.30 0.040 0.221
BMI_conception 1 0.019 0.0194 0.73 0.022 0.664
HLA.6DRML 2 0.057 0.0287 1.08 0.066 0.363
T1Dstatus 1 0.031 0.0313 1.18 0.036 0.307
Residuals 22 0.586 0.0266 0.675
Total 31 0.867 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.307Beta diversity Plot
12.4.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.077 0.0258 0.906 0.082 0.617
Nulliparous 1 0.030 0.0302 1.058 0.032 0.355
Age_LMP 1 0.037 0.0367 1.286 0.039 0.230
BMI_conception 1 0.044 0.0438 1.534 0.046 0.102
HLA.6DRML 2 0.059 0.0295 1.035 0.062 0.406
T1Dstatus 1 0.073 0.0733 2.570 0.077 0.008 **
Residuals 22 0.627 0.0285 0.662
Total 31 0.948 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.008Beta diversity Plot
12.4.5 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.111 0.0555 2.37 0.079 0.51
seqRun 3 0.156 0.0521 2.22 0.112 0.66
Age 1 0.050 0.0505 2.15 0.036 0.93
Parity 1 0.090 0.0901 3.84 0.064 0.27
BMI 1 0.080 0.0803 3.42 0.057 0.17
Tri 2 0.042 0.0209 0.89 0.030 0.28
Residuals 37 0.868 0.0235 0.621 0.73
Total 47 1.398 1.000 Beta diversity Plot
12.4.6 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.134 0.0670 3.26 0.107 0.32
seqRun 3 0.162 0.0540 2.62 0.129 0.87
Age 1 0.102 0.1018 4.95 0.081 0.13
Parity 1 0.028 0.0283 1.38 0.023 0.96
BMI 1 0.038 0.0383 1.86 0.031 0.18
Tri 2 0.026 0.0128 0.62 0.020 0.57
Residuals 37 0.761 0.0206 0.608 0.61
Total 47 1.251 1.000 Beta diversity Plot
12.5 Differential abundance analysis
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3
Down 0 0 0 3 0 0 5 1 0
NotSig 5480 5480 5480 5421 5470 5480 5421 4846 5480
Up 0 0 0 56 10 0 54 633 0
T1DT1vsT3 noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 30 0 0 10
NotSig 4838 5474 5480 5440
Up 612 6 0 30Results for contrasts with significant differentially abundant strains shown below
12.5.1 Across all trimesters (T1D vs non-T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
3 K08681 1.13 5.20e-05 0.0894 1.963 100.0 0.823 100.0
5 K13788 1.34 4.21e-05 0.0894 0.276 93.8 0.091 83.3
1 K03465 1.37 7.95e-05 0.0894 2.694 100.0 1.429 100.0
2 K04092 1.52 8.16e-05 0.0894 0.420 70.8 0.081 39.6
4 K09163 1.74 7.16e-05 0.0894 0.808 100.0 0.252 95.812.5.2 Only Trimester 1 (nonT1D vs T1D)
Function LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 K03815 -1.229 5.91e-05 0.0540 0 50.0 0.001 50.0
3 K10986 -1.034 4.57e-05 0.0540 0 43.8 0.000 56.2
4 K15721 -1.030 1.02e-04 0.0623 0 31.2 0.000 56.2
2 K04784 -0.961 2.81e-05 0.0540 0 31.2 0.000 56.212.5.3 Only Trimester 2 (nonT1D vs T1D)
[1] "No DA taxa found"12.5.4 Only Trimester 3 (nonT1D vs T1D)
Function LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
74 K02852 -2.314 3.22e-04 0.043062 0.007 81.2 0.024 100.0
21 K00936 -2.093 5.10e-04 0.048661 0.004 87.5 0.007 93.8
100 K04045 -1.622 8.57e-04 0.059982 0.000 81.2 0.002 93.8
93 K03735 -1.560 2.33e-03 0.084572 0.001 100.0 0.003 100.0
186 K13630 -1.316 3.54e-03 0.098070 0.001 18.8 0.002 50.0
110 K05834 -1.316 2.45e-03 0.085689 0.001 43.8 0.002 62.5
5 K00242 -1.297 1.52e-03 0.073171 0.001 50.0 0.002 56.2
204 K19000 -1.259 9.94e-04 0.062435 0.000 37.5 0.001 62.5
182 K12524 -1.237 2.96e-03 0.091623 0.004 100.0 0.008 100.0
142 K07443 -1.232 3.82e-03 0.099601 0.013 100.0 0.020 100.0
122 K06891 -1.217 2.51e-03 0.085851 0.001 56.2 0.002 56.2
16 K00832 -1.215 2.62e-03 0.086178 0.000 62.5 0.001 75.0
203 K18929 -1.158 1.46e-03 0.072717 0.013 100.0 0.025 100.0
10 K00568 -1.133 3.79e-03 0.099601 0.001 56.2 0.002 56.2
103 K04334 -1.059 5.82e-04 0.052949 0.000 43.8 0.001 62.5
175 K10973 -1.054 3.53e-03 0.098070 0.000 50.0 0.001 62.5
145 K07470 -1.049 2.82e-03 0.088368 0.000 43.8 0.002 68.8
151 K07803 -1.026 1.70e-03 0.073171 0.000 43.8 0.002 62.5
107 K05367 -1.024 7.08e-04 0.054892 0.016 100.0 0.026 100.0
162 K09712 -1.020 1.33e-03 0.072717 0.000 25.0 0.001 56.2
195 K16326 -1.020 1.76e-03 0.073171 0.000 43.8 0.001 62.5
137 K07165 -0.975 1.45e-03 0.072717 0.000 31.2 0.001 50.0
64 K02394 -0.961 2.26e-03 0.083500 0.000 56.2 0.001 68.8
39 K01483 -0.959 2.44e-03 0.085689 0.000 31.2 0.001 56.2
91 K03668 -0.954 3.77e-03 0.099601 0.000 31.2 0.001 56.2
69 K02565 -0.943 3.71e-03 0.099601 0.000 56.2 0.001 81.2
113 K05984 -0.928 2.19e-03 0.082593 0.000 56.2 0.001 75.0
172 K10680 -0.918 2.70e-03 0.086178 0.000 56.2 0.001 68.8
98 K04024 -0.908 1.55e-03 0.073171 0.000 50.0 0.001 81.2
198 K17247 -0.899 3.06e-03 0.091623 0.000 56.2 0.001 68.8
46 K01791 -0.867 2.46e-04 0.040944 0.037 100.0 0.068 100.0
154 K08162 -0.853 1.22e-03 0.068945 0.000 56.2 0.001 62.5
20 K00929 -0.814 1.87e-03 0.075508 0.044 100.0 0.067 100.0
78 K03281 -0.805 2.41e-03 0.085689 0.054 100.0 0.078 100.0
181 K12343 -0.789 2.64e-03 0.086178 0.040 100.0 0.058 100.0
201 K18691 -0.787 1.79e-03 0.073171 0.037 100.0 0.057 100.0
97 K03832 -0.753 3.63e-03 0.099102 0.068 100.0 0.111 100.0
38 K01468 -0.740 3.79e-03 0.099601 0.052 100.0 0.080 100.0
83 K03474 -0.726 1.79e-03 0.073171 0.046 100.0 0.067 100.0
99 K04032 -0.676 3.35e-03 0.095030 0.000 50.0 0.001 56.2
95 K03771 -0.675 3.03e-03 0.091623 0.048 100.0 0.071 100.0
75 K03118 -0.669 1.99e-03 0.079203 0.048 100.0 0.069 100.0
43 K01719 -0.668 2.70e-03 0.086178 0.049 100.0 0.071 100.0
180 K12137 -0.662 3.58e-03 0.098621 0.000 62.5 0.001 68.8
96 K03797 -0.561 1.98e-03 0.079203 0.154 100.0 0.220 100.0
128 K06997 0.564 3.06e-03 0.091623 0.050 100.0 0.040 100.0
31 K01129 0.603 3.00e-03 0.091623 0.050 100.0 0.040 100.0
61 K02110 0.650 1.15e-03 0.067899 0.164 100.0 0.121 100.0
14 K00763 0.654 2.63e-03 0.086178 0.055 100.0 0.044 100.0
44 K01756 0.745 2.63e-03 0.086178 0.074 100.0 0.055 100.0
60 K02108 0.782 1.10e-03 0.066047 0.065 100.0 0.043 100.0
140 K07317 0.811 2.12e-03 0.081547 0.001 56.2 0.000 37.5
56 K02037 0.813 1.09e-03 0.066047 0.044 100.0 0.028 100.0
120 K06608 0.845 1.50e-03 0.073171 0.001 50.0 0.000 50.0
133 K07040 0.857 2.67e-03 0.086178 0.035 100.0 0.019 100.0
17 K00868 0.878 5.20e-04 0.048661 0.043 100.0 0.026 100.0
23 K00941 0.887 2.76e-04 0.040944 0.055 100.0 0.038 100.0
136 K07090 0.907 1.76e-03 0.073171 0.043 100.0 0.030 100.0
124 K06958 0.918 2.70e-03 0.086178 0.024 100.0 0.013 100.0
101 K04066 0.933 1.16e-03 0.067899 0.033 100.0 0.019 100.0
177 K11189 0.936 2.18e-03 0.082593 0.105 100.0 0.067 100.0
11 K00611 0.941 6.52e-04 0.054892 0.081 100.0 0.055 100.0
19 K00897 0.979 2.70e-03 0.086178 0.001 50.0 0.000 31.2
76 K03151 1.002 3.54e-03 0.098070 0.038 100.0 0.024 100.0
15 K00821 1.006 2.72e-03 0.086298 0.040 100.0 0.027 100.0
25 K00975 1.025 1.55e-03 0.073171 0.101 100.0 0.065 100.0
123 K06901 1.027 1.25e-03 0.068945 0.049 100.0 0.031 100.0
89 K03574 1.034 1.58e-04 0.040944 0.075 100.0 0.040 100.0
146 K07574 1.036 2.01e-03 0.079333 0.042 100.0 0.029 100.0
77 K03216 1.043 5.24e-04 0.048661 0.040 100.0 0.024 100.0
163 K09747 1.048 2.08e-03 0.081394 0.048 100.0 0.029 100.0
134 K07042 1.051 7.83e-04 0.056484 0.041 100.0 0.025 100.0
164 K09762 1.054 3.69e-03 0.099601 0.024 100.0 0.012 100.0
105 K04488 1.057 2.22e-03 0.082723 0.059 100.0 0.036 100.0
114 K06024 1.057 3.81e-03 0.099601 0.025 100.0 0.014 100.0
143 K07454 1.062 2.75e-04 0.040944 0.001 68.8 0.000 43.8
153 K07979 1.066 2.13e-03 0.081547 0.058 100.0 0.032 100.0
118 K06346 1.066 3.44e-03 0.096738 0.025 100.0 0.015 100.0
45 K01786 1.071 3.28e-03 0.093698 0.032 100.0 0.015 100.0
49 K01996 1.074 3.02e-03 0.091623 0.055 100.0 0.034 100.0
111 K05896 1.082 1.43e-03 0.072717 0.020 100.0 0.012 100.0
169 K10117 1.089 2.47e-03 0.085689 0.075 100.0 0.041 100.0
51 K02026 1.093 1.82e-03 0.073942 0.077 100.0 0.050 100.0
50 K02025 1.094 1.60e-03 0.073171 0.060 100.0 0.035 100.0
106 K04758 1.103 1.22e-03 0.068945 0.095 100.0 0.053 100.0
53 K02028 1.110 2.44e-04 0.040944 0.085 100.0 0.045 100.0
190 K15023 1.116 2.36e-03 0.084897 0.003 100.0 0.001 87.5
30 K01090 1.120 3.10e-03 0.091891 0.015 100.0 0.006 100.0
22 K00937 1.122 2.45e-04 0.040944 0.029 100.0 0.015 100.0
87 K03523 1.124 1.39e-03 0.072717 0.029 100.0 0.016 100.0
168 K10112 1.126 4.05e-04 0.045251 0.081 100.0 0.046 100.0
165 K09772 1.132 1.35e-03 0.072717 0.030 100.0 0.016 100.0
58 K02072 1.132 2.68e-03 0.086178 0.037 100.0 0.023 100.0
104 K04487 1.134 4.15e-04 0.045251 0.047 100.0 0.027 100.0
116 K06200 1.135 5.99e-04 0.052949 0.039 100.0 0.023 100.0
125 K06960 1.140 7.11e-04 0.054892 0.070 100.0 0.037 100.0
159 K08884 1.141 1.65e-03 0.073171 0.034 100.0 0.017 100.0
174 K10907 1.147 7.34e-04 0.055082 0.051 100.0 0.028 100.0
18 K00878 1.148 3.49e-04 0.043062 0.039 100.0 0.019 100.0
55 K02030 1.150 2.61e-04 0.040944 0.080 100.0 0.043 100.0
152 K07816 1.160 2.29e-03 0.083671 0.046 100.0 0.018 100.0
81 K03338 1.161 1.85e-04 0.040944 0.002 75.0 0.000 37.5
92 K03724 1.165 4.35e-04 0.045251 0.003 100.0 0.000 93.8
24 K00965 1.172 3.54e-04 0.043062 0.030 100.0 0.016 100.0
27 K00995 1.174 3.44e-05 0.019424 0.096 100.0 0.046 100.0
41 K01693 1.176 2.17e-04 0.040944 0.051 100.0 0.027 100.0
112 K05967 1.189 8.87e-04 0.059982 0.002 75.0 0.000 68.8
160 K09157 1.192 6.80e-04 0.054892 0.061 100.0 0.034 100.0
129 K07003 1.195 8.68e-04 0.059982 0.027 100.0 0.012 100.0
148 K07738 1.199 1.37e-04 0.040944 0.044 100.0 0.020 100.0
66 K02433 1.202 2.56e-04 0.040944 0.039 100.0 0.017 100.0
36 K01356 1.205 1.77e-04 0.040944 0.083 100.0 0.050 100.0
29 K01026 1.208 2.87e-03 0.089323 0.002 62.5 0.000 50.0
12 K00620 1.221 1.93e-04 0.040944 0.051 100.0 0.030 100.0
52 K02027 1.222 2.02e-04 0.040944 0.057 100.0 0.029 100.0
156 K08316 1.231 2.09e-03 0.081394 0.015 100.0 0.006 100.0
119 K06378 1.232 3.15e-03 0.092240 0.014 100.0 0.007 100.0
48 K01989 1.233 2.48e-03 0.085689 0.048 100.0 0.025 100.0
144 K07467 1.233 1.54e-03 0.073171 0.005 93.8 0.001 87.5
1 K00008 1.239 1.24e-03 0.068945 0.020 100.0 0.009 100.0
178 K11358 1.239 1.02e-03 0.063002 0.035 100.0 0.021 100.0
202 K18828 1.244 3.20e-03 0.092738 0.006 100.0 0.001 81.2
109 K05832 1.247 3.72e-03 0.099601 0.027 100.0 0.011 100.0
67 K02434 1.254 1.34e-04 0.040944 0.044 100.0 0.020 100.0
170 K10118 1.260 8.83e-04 0.059982 0.064 100.0 0.032 100.0
32 K01193 1.275 1.00e-03 0.062435 0.049 100.0 0.025 100.0
171 K10119 1.287 6.55e-04 0.054892 0.065 100.0 0.030 100.0
68 K02435 1.289 3.52e-04 0.043062 0.038 100.0 0.016 100.0
184 K13570 1.289 1.57e-03 0.073171 0.003 56.2 0.000 18.8
37 K01439 1.296 1.66e-03 0.073171 0.024 100.0 0.013 100.0
85 K03488 1.313 2.20e-03 0.082593 0.026 100.0 0.013 100.0
2 K00016 1.327 1.65e-03 0.073171 0.025 100.0 0.009 100.0
7 K00375 1.329 3.72e-04 0.044315 0.022 100.0 0.011 100.0
88 K03529 1.335 1.57e-03 0.073171 0.006 100.0 0.002 100.0
126 K06972 1.336 1.46e-03 0.072717 0.010 100.0 0.004 100.0
138 K07166 1.348 3.29e-04 0.043062 0.044 100.0 0.024 100.0
132 K07033 1.364 3.76e-03 0.099601 0.009 100.0 0.004 100.0
54 K02029 1.414 2.23e-05 0.015257 0.101 100.0 0.041 100.0
70 K02588 1.427 1.41e-03 0.072717 0.005 93.8 0.001 93.8
57 K02049 1.433 2.49e-03 0.085689 0.018 100.0 0.006 100.0
90 K03660 1.438 1.65e-03 0.073171 0.009 100.0 0.004 100.0
80 K03337 1.445 1.69e-03 0.073171 0.004 93.8 0.002 100.0
9 K00563 1.450 1.76e-03 0.073171 0.029 100.0 0.011 100.0
147 K07726 1.454 2.58e-03 0.086178 0.016 100.0 0.005 100.0
86 K03518 1.464 2.14e-04 0.040944 0.018 100.0 0.008 100.0
158 K08681 1.471 7.21e-06 0.007215 0.024 100.0 0.007 100.0
65 K02406 1.479 1.76e-03 0.073171 0.035 100.0 0.012 100.0
28 K00997 1.480 5.02e-04 0.048661 0.024 100.0 0.008 100.0
4 K00209 1.483 1.70e-03 0.073171 0.006 87.5 0.000 56.2
115 K06042 1.485 7.60e-05 0.032777 0.018 100.0 0.007 100.0
71 K02744 1.486 2.54e-03 0.086178 0.004 93.8 0.001 87.5
199 K17686 1.506 8.63e-04 0.059982 0.013 100.0 0.004 100.0
35 K01354 1.508 1.40e-03 0.072717 0.004 87.5 0.001 93.8
205 K19310 1.517 1.82e-04 0.040944 0.036 100.0 0.014 100.0
82 K03465 1.523 1.56e-04 0.040944 0.031 100.0 0.014 100.0
121 K06859 1.525 7.82e-04 0.056484 0.003 87.5 0.000 62.5
73 K02851 1.530 3.01e-03 0.091623 0.009 100.0 0.003 100.0
63 K02203 1.539 2.97e-04 0.042834 0.014 100.0 0.005 100.0
117 K06215 1.541 8.95e-06 0.007215 0.034 100.0 0.013 100.0
94 K03767 1.544 3.41e-03 0.096268 0.011 100.0 0.003 100.0
131 K07012 1.549 5.95e-04 0.052949 0.009 100.0 0.005 100.0
40 K01494 1.555 4.43e-04 0.045251 0.013 100.0 0.004 100.0
13 K00690 1.566 2.60e-04 0.040944 0.015 100.0 0.006 100.0
141 K07442 1.576 3.15e-03 0.092240 0.006 93.8 0.001 100.0
127 K06987 1.582 1.18e-03 0.068215 0.010 100.0 0.004 100.0
84 K03484 1.593 7.10e-04 0.054892 0.018 100.0 0.005 100.0
176 K11050 1.593 1.12e-03 0.066773 0.011 100.0 0.004 93.8
193 K16209 1.613 2.37e-03 0.084897 0.006 87.5 0.001 100.0
197 K16925 1.616 1.37e-03 0.072717 0.005 87.5 0.001 93.8
173 K10805 1.650 3.63e-03 0.099102 0.005 93.8 0.001 81.2
33 K01198 1.657 7.08e-04 0.054892 0.027 100.0 0.007 100.0
200 K17810 1.660 3.89e-04 0.045251 0.004 100.0 0.001 100.0
183 K13527 1.661 1.60e-03 0.073171 0.006 87.5 0.001 93.8
167 K10008 1.689 3.24e-03 0.093574 0.007 93.8 0.002 100.0
161 K09163 1.694 7.64e-04 0.056484 0.009 100.0 0.003 100.0
6 K00324 1.711 2.29e-03 0.083671 0.011 100.0 0.003 100.0
179 K11928 1.720 7.73e-06 0.007215 0.035 100.0 0.013 100.0
192 K16148 1.724 1.37e-03 0.072717 0.006 87.5 0.001 93.8
139 K07260 1.725 7.02e-04 0.054892 0.028 100.0 0.012 100.0
79 K03335 1.725 8.37e-05 0.032777 0.004 81.2 0.001 62.5
108 K05794 1.740 4.21e-04 0.045251 0.005 87.5 0.001 93.8
194 K16235 1.780 1.62e-03 0.073171 0.007 87.5 0.001 87.5
157 K08372 1.815 4.16e-04 0.045251 0.009 100.0 0.002 100.0
166 K10007 1.826 9.35e-04 0.062148 0.006 87.5 0.001 100.0
149 K07768 1.829 9.62e-04 0.062148 0.007 87.5 0.001 93.8
8 K00395 1.840 2.64e-04 0.040944 0.009 100.0 0.003 100.0
150 K07776 1.843 9.45e-04 0.062148 0.006 93.8 0.002 93.8
3 K00171 1.857 9.22e-06 0.007215 0.006 93.8 0.001 87.5
185 K13571 1.859 7.24e-04 0.055082 0.007 87.5 0.001 100.0
42 K01697 1.868 9.98e-04 0.062435 0.007 87.5 0.001 93.8
59 K02077 1.873 9.64e-04 0.062148 0.011 100.0 0.002 100.0
135 K07080 1.873 3.28e-04 0.043062 0.010 100.0 0.002 100.0
187 K13787 1.903 8.22e-05 0.032777 0.010 100.0 0.002 100.0
130 K07006 1.930 1.78e-03 0.073171 0.008 87.5 0.001 81.2
26 K00990 1.943 1.06e-06 0.002904 0.004 75.0 0.000 56.2
47 K01807 2.008 1.97e-04 0.040944 0.014 100.0 0.003 100.0
155 K08300 2.015 4.46e-04 0.045251 0.009 87.5 0.000 87.5
72 K02822 2.024 5.09e-04 0.048661 0.006 100.0 0.001 93.8
189 K13940 2.029 1.37e-04 0.040944 0.008 100.0 0.001 100.0
62 K02122 2.064 3.50e-04 0.043062 0.010 87.5 0.001 87.5
188 K13788 2.070 1.30e-07 0.000712 0.003 100.0 0.000 68.8
102 K04092 2.114 3.39e-06 0.006184 0.006 68.8 0.000 31.2
196 K16784 2.280 1.04e-04 0.037979 0.010 87.5 0.001 100.0
191 K16147 2.384 3.54e-05 0.019424 0.009 87.5 0.000 81.2
34 K01304 2.432 5.61e-05 0.027927 0.007 81.2 0.000 62.512.5.5 T1 vs T2 (All data)
Function LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev% T3:mean% T3Prev%
1 K02339 0.502 3.09e-05 0.024195 0.001 60.9 0.000 32.5 0 21.2
2 K02471 0.580 1.05e-04 0.052281 0.002 91.3 0.001 82.5 0 57.6
3 K05589 0.619 3.15e-04 0.096449 0.002 65.2 0.000 42.5 0 27.3
4 K06212 0.589 8.53e-08 0.000234 0.001 69.6 0.000 45.0 0 36.4
5 K07234 0.628 7.49e-08 0.000234 0.001 78.3 0.000 55.0 0 36.4
6 K09780 0.503 1.87e-04 0.068223 0.001 56.5 0.000 25.0 0 21.2
7 K09801 0.640 9.98e-07 0.001367 0.001 69.6 0.000 32.5 0 27.312.5.6 T2 vs T3 (All data)
[1] "No DA taxa"12.5.7 T1 vs T3 (All data)
Function LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev% T3:mean% T3Prev%
1 K00368 0.655 7.03e-08 4.14e-05 0.001 65.2 0.000 60.0 0.000 30.3
2 K00955 1.104 3.43e-05 6.95e-03 0.003 69.6 0.001 47.5 0.001 57.6
3 K01166 0.703 1.74e-07 6.79e-05 0.001 69.6 0.000 52.5 0.000 33.3
4 K01226 -0.790 6.37e-04 5.64e-02 0.002 87.0 0.002 95.0 0.002 100.0
5 K01668 0.563 9.89e-08 4.93e-05 0.000 73.9 0.000 50.0 0.000 33.3
6 K01674 0.678 1.05e-05 2.73e-03 0.001 69.6 0.000 45.0 0.000 33.3
7 K02012 0.962 1.29e-04 1.81e-02 0.003 78.3 0.002 80.0 0.001 75.8
8 K02062 0.768 3.00e-06 8.21e-04 0.001 82.6 0.000 67.5 0.000 48.5
9 K02339 0.584 1.95e-06 5.95e-04 0.001 60.9 0.000 32.5 0.000 21.2
10 K02344 0.568 8.13e-05 1.27e-02 0.001 60.9 0.000 32.5 0.000 27.3
11 K02471 0.938 4.05e-09 5.03e-06 0.002 91.3 0.001 82.5 0.000 57.6
12 K02496 0.643 2.42e-04 3.04e-02 0.001 91.3 0.001 80.0 0.000 69.7
13 K02554 -0.597 1.21e-04 1.79e-02 0.000 47.8 0.001 42.5 0.001 63.6
14 K03074 0.817 6.34e-05 1.09e-02 0.003 87.0 0.003 82.5 0.002 57.6
15 K03656 0.700 1.89e-05 4.31e-03 0.001 91.3 0.001 77.5 0.000 63.6
16 K03923 0.621 7.75e-04 6.27e-02 0.001 73.9 0.001 77.5 0.000 69.7
17 K04073 -0.532 3.03e-04 3.33e-02 0.000 43.5 0.001 47.5 0.001 60.6
18 K05589 0.896 5.40e-07 1.85e-04 0.002 65.2 0.000 42.5 0.000 27.3
19 K05685 0.618 4.59e-09 5.03e-06 0.000 82.6 0.000 57.5 0.000 33.3
20 K06194 0.549 3.92e-05 7.42e-03 0.001 82.6 0.000 67.5 0.000 78.8
21 K06212 0.696 9.11e-10 1.66e-06 0.001 69.6 0.000 45.0 0.000 36.4
22 K07084 0.500 2.20e-06 6.35e-04 0.001 65.2 0.000 60.0 0.000 36.4
23 K07121 0.525 1.03e-03 7.46e-02 0.001 82.6 0.001 82.5 0.000 72.7
24 K07234 0.846 8.71e-12 4.78e-08 0.001 78.3 0.000 55.0 0.000 36.4
25 K07803 -0.627 1.63e-04 2.24e-02 0.000 13.0 0.001 37.5 0.001 51.5
26 K08310 0.623 6.38e-04 5.64e-02 0.002 69.6 0.001 60.0 0.001 60.6
27 K09780 0.575 2.76e-05 6.05e-03 0.001 56.5 0.000 25.0 0.000 21.2
28 K09801 0.857 5.55e-10 1.52e-06 0.001 69.6 0.000 32.5 0.000 27.3
29 K09824 0.722 3.03e-05 6.38e-03 0.001 73.9 0.001 72.5 0.000 63.6
30 K11211 0.700 1.59e-08 1.24e-05 0.001 73.9 0.000 50.0 0.000 27.3
31 K11605 0.687 3.73e-04 3.78e-02 0.001 87.0 0.001 72.5 0.000 60.6
32 K11606 0.574 6.78e-04 5.89e-02 0.001 78.3 0.000 75.0 0.000 57.6
33 K11607 0.596 1.08e-06 3.49e-04 0.001 65.2 0.000 60.0 0.000 30.3
34 K12982 0.696 1.39e-07 5.88e-05 0.001 65.2 0.000 55.0 0.000 30.3
35 K12984 0.575 3.93e-05 7.42e-03 0.001 65.2 0.000 57.5 0.000 33.3
36 K13634 0.678 1.33e-08 1.21e-05 0.001 60.9 0.000 52.5 0.000 27.3
37 K15461 0.576 7.55e-08 4.14e-05 0.001 87.0 0.000 75.0 0.000 54.5
38 K15984 0.650 8.79e-05 1.34e-02 0.001 69.6 0.001 55.0 0.000 27.3
39 K17733 1.330 3.11e-04 3.33e-02 0.005 60.9 0.002 55.0 0.002 54.5
40 K18893 0.598 4.25e-07 1.55e-04 0.001 69.6 0.000 67.5 0.000 33.3
41 K19509 -0.530 3.81e-04 3.80e-02 0.000 43.5 0.001 57.5 0.001 57.612.5.8 T1 vs T2 (in women with T1D)
Function LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
70 K18120 -0.748 3.22e-03 0.03288 0.001 100.0 0.002 100
60 K09740 -0.677 1.18e-02 0.08868 0.002 100.0 0.004 100
51 K07034 -0.662 7.61e-03 0.06236 0.000 50.0 0.001 70
7 K00782 -0.563 1.05e-02 0.08017 0.032 100.0 0.045 100
44 K04784 0.502 4.55e-04 0.01253 0.001 58.3 0.000 60
32 K03216 0.518 1.36e-02 0.09912 0.032 100.0 0.026 100
13 K01355 0.534 2.82e-04 0.01182 0.001 58.3 0.000 50
73 K18893 0.535 5.97e-04 0.01319 0.001 58.3 0.000 65
53 K07090 0.542 7.87e-03 0.06411 0.039 100.0 0.027 100
66 K14170 0.553 9.39e-03 0.07372 0.022 100.0 0.017 100
54 K07478 0.559 2.33e-03 0.02648 0.097 100.0 0.072 100
25 K02339 0.564 5.04e-04 0.01266 0.001 50.0 0.000 25
55 K07738 0.565 9.55e-03 0.07465 0.033 100.0 0.021 100
38 K03625 0.567 3.47e-03 0.03487 0.056 100.0 0.043 100
61 K09780 0.579 1.70e-03 0.02130 0.001 58.3 0.000 20
43 K03815 0.580 2.31e-03 0.02644 0.002 50.0 0.001 40
2 K00054 0.581 8.68e-04 0.01496 0.001 58.3 0.000 55
17 K02028 0.584 5.67e-03 0.04924 0.055 100.0 0.045 100
40 K03724 0.585 9.41e-03 0.07376 0.001 100.0 0.000 100
19 K02030 0.586 7.53e-03 0.06196 0.055 100.0 0.044 100
26 K02433 0.619 6.90e-03 0.05766 0.024 100.0 0.019 100
6 K00626 0.625 8.28e-03 0.06672 0.038 100.0 0.025 100
52 K07040 0.626 2.02e-03 0.02387 0.028 100.0 0.019 100
42 K03785 0.643 6.85e-03 0.05736 0.021 100.0 0.012 100
16 K01848 0.655 3.39e-03 0.03425 0.001 75.0 0.000 60
24 K02283 0.664 1.00e-02 0.07763 0.024 100.0 0.014 100
41 K03746 0.667 9.15e-03 0.07234 0.004 75.0 0.001 50
27 K02471 0.675 8.80e-04 0.01512 0.002 91.7 0.000 80
68 K15582 0.678 5.08e-03 0.04565 0.033 100.0 0.022 100
21 K02062 0.679 1.94e-03 0.02308 0.002 83.3 0.000 75
45 K05589 0.690 3.16e-03 0.03252 0.002 50.0 0.000 30
5 K00375 0.696 7.61e-03 0.06236 0.015 100.0 0.010 100
63 K11605 0.701 7.24e-03 0.06008 0.002 91.7 0.001 80
3 K00124 0.702 1.27e-02 0.09428 0.003 100.0 0.001 95
8 K00878 0.710 1.68e-03 0.02130 0.026 100.0 0.017 100
49 K06446 0.710 1.37e-03 0.01899 0.001 100.0 0.001 95
36 K03500 0.717 1.11e-03 0.01682 0.018 100.0 0.011 100
67 K15256 0.735 9.36e-03 0.07366 0.003 66.7 0.001 75
18 K02029 0.738 1.41e-03 0.01933 0.061 100.0 0.042 100
57 K08310 0.742 3.03e-03 0.03155 0.003 66.7 0.001 60
1 K00020 0.743 3.15e-03 0.03244 0.003 100.0 0.000 95
46 K05594 0.748 5.45e-03 0.04795 0.002 66.7 0.001 45
15 K01524 0.766 1.36e-02 0.09929 0.020 100.0 0.014 100
20 K02035 0.767 1.66e-03 0.02120 0.021 100.0 0.012 100
58 K08316 0.770 6.37e-03 0.05399 0.011 100.0 0.006 100
29 K02573 0.772 1.04e-02 0.08011 0.006 100.0 0.003 100
11 K00997 0.780 8.72e-03 0.06945 0.014 100.0 0.009 100
47 K05832 0.781 1.01e-02 0.07811 0.014 100.0 0.009 100
64 K11606 0.793 6.40e-04 0.01343 0.002 83.3 0.000 75
14 K01426 0.798 1.02e-02 0.07845 0.002 100.0 0.001 100
56 K08151 0.798 7.68e-05 0.00679 0.001 66.7 0.001 45
71 K18476 0.801 4.51e-05 0.00608 0.001 75.0 0.001 35
65 K13292 0.806 9.32e-04 0.01566 0.019 100.0 0.011 100
33 K03306 0.808 6.29e-03 0.05340 0.004 100.0 0.002 100
30 K03060 0.809 3.60e-03 0.03569 0.021 100.0 0.013 100
62 K09801 0.809 5.81e-06 0.00436 0.001 58.3 0.000 25
12 K01040 0.827 2.76e-03 0.02954 0.003 100.0 0.002 100
39 K03646 0.834 4.45e-03 0.04180 0.002 100.0 0.001 95
28 K02552 0.835 1.20e-02 0.09023 0.005 100.0 0.002 100
48 K06182 0.837 5.71e-03 0.04941 0.013 100.0 0.007 100
72 K18672 0.845 1.32e-02 0.09710 0.010 100.0 0.005 95
37 K03610 0.860 5.17e-03 0.04619 0.009 100.0 0.004 100
23 K02203 0.886 2.99e-03 0.03128 0.008 100.0 0.004 100
34 K03413 0.890 2.06e-03 0.02418 0.020 100.0 0.010 100
22 K02193 0.902 2.54e-03 0.02772 0.004 100.0 0.002 95
59 K08978 0.915 4.98e-03 0.04501 0.014 100.0 0.007 90
74 K19294 0.919 1.23e-03 0.01772 0.002 91.7 0.000 90
31 K03087 0.954 1.12e-02 0.08489 0.003 58.3 0.001 65
4 K00209 0.985 3.65e-03 0.03613 0.002 91.7 0.001 75
50 K06864 1.028 8.39e-03 0.06723 0.008 100.0 0.003 100
35 K03458 1.031 4.35e-03 0.04120 0.008 100.0 0.004 100
10 K00968 1.033 1.03e-02 0.07918 0.004 75.0 0.002 55
9 K00955 1.099 2.39e-03 0.02663 0.004 75.0 0.001 45
69 K17733 1.327 7.77e-03 0.06342 0.007 66.7 0.002 6012.5.9 T2 vs T3 (in women with T1D)
Function LogFC P.Val adj.P.Val T2:mean% T2Prev% T3:mean% T3Prev%
3 K01819 -0.613 0.00157 0.572 0.000 40 0.001 56.2
4 K17733 0.519 0.23414 1.000 0.002 60 0.001 50.0
1 K00955 0.568 0.06656 1.000 0.001 45 0.000 50.0
2 K00968 0.587 0.09661 1.000 0.002 55 0.001 56.212.5.10 T1 vs T3 (in women with T1D)
Function LogFC P.Val adj.P.Val T1:mean% T1Prev% T3:mean% T3Prev%
19 K00936 -1.099 1.01e-02 0.07302 0.004 91.7 0.007 93.8
186 K18929 -1.007 1.49e-04 0.00982 0.015 100.0 0.025 100.0
131 K07803 -0.895 1.48e-04 0.00982 0.001 16.7 0.002 62.5
128 K07484 -0.827 7.60e-03 0.06041 0.017 100.0 0.024 100.0
27 K01133 -0.824 3.87e-03 0.03764 0.010 100.0 0.017 100.0
185 K18928 -0.786 2.86e-03 0.03052 0.014 100.0 0.023 100.0
106 K05714 -0.775 9.57e-04 0.01750 0.001 33.3 0.002 75.0
75 K02554 -0.751 5.81e-04 0.01560 0.001 41.7 0.002 56.2
134 K08161 -0.728 8.16e-04 0.01659 0.000 66.7 0.001 75.0
156 K11201 -0.720 1.28e-02 0.08536 0.000 66.7 0.003 68.8
161 K12137 -0.699 2.78e-05 0.00625 0.000 25.0 0.001 68.8
99 K04073 -0.688 9.49e-04 0.01750 0.001 41.7 0.002 62.5
9 K00336 -0.677 1.16e-02 0.07984 0.012 100.0 0.021 100.0
153 K10709 -0.648 1.25e-02 0.08437 0.000 50.0 0.002 68.8
115 K06908 -0.634 8.11e-03 0.06328 0.001 16.7 0.001 62.5
144 K09470 -0.611 3.04e-04 0.01352 0.000 41.7 0.001 62.5
16 K00782 -0.609 6.29e-03 0.05277 0.032 100.0 0.048 100.0
10 K00347 -0.565 8.29e-03 0.06373 0.035 100.0 0.055 100.0
135 K08162 -0.563 2.81e-03 0.03029 0.001 50.0 0.001 62.5
30 K01271 -0.559 1.55e-02 0.09757 0.017 100.0 0.023 100.0
42 K01791 -0.551 1.10e-03 0.01856 0.045 100.0 0.068 100.0
139 K08318 -0.550 4.85e-03 0.04391 0.000 16.7 0.001 50.0
4 K00175 -0.543 4.56e-03 0.04215 0.072 100.0 0.111 100.0
61 K02121 -0.539 1.60e-02 0.09954 0.022 100.0 0.032 100.0
145 K09472 -0.510 2.76e-03 0.02993 0.000 25.0 0.001 62.5
140 K08483 0.500 5.01e-03 0.04501 0.035 100.0 0.029 100.0
105 K05685 0.506 2.35e-04 0.01173 0.000 75.0 0.000 37.5
155 K10979 0.508 3.35e-03 0.03406 0.000 66.7 0.000 25.0
174 K15461 0.516 2.81e-04 0.01293 0.001 83.3 0.000 56.2
71 K02455 0.518 1.22e-02 0.08295 0.003 58.3 0.001 50.0
117 K06958 0.529 1.51e-02 0.09579 0.016 100.0 0.013 100.0
7 K00248 0.531 4.13e-03 0.03911 0.013 100.0 0.010 100.0
122 K07124 0.537 8.23e-03 0.06368 0.023 100.0 0.018 100.0
20 K00937 0.538 1.26e-02 0.08446 0.017 100.0 0.015 100.0
66 K02339 0.539 9.51e-04 0.01750 0.001 50.0 0.000 12.5
173 K14475 0.541 1.42e-02 0.09149 0.000 58.3 0.000 31.2
88 K03574 0.541 5.02e-03 0.04501 0.053 100.0 0.040 100.0
170 K14170 0.550 1.06e-02 0.07520 0.022 100.0 0.018 100.0
107 K05874 0.550 3.90e-03 0.03772 0.001 58.3 0.000 31.2
11 K00368 0.552 5.42e-04 0.01529 0.001 58.3 0.000 31.2
166 K13634 0.553 3.64e-04 0.01365 0.001 50.0 0.000 37.5
102 K04759 0.570 5.55e-03 0.04843 0.035 100.0 0.029 100.0
87 K03561 0.570 1.26e-02 0.08466 0.089 100.0 0.069 100.0
36 K01515 0.570 1.61e-02 0.09954 0.025 100.0 0.020 100.0
119 K07095 0.571 2.38e-03 0.02747 0.074 100.0 0.056 100.0
141 K08591 0.571 8.27e-03 0.06368 0.040 100.0 0.030 100.0
48 K01950 0.572 3.92e-03 0.03793 0.111 100.0 0.080 100.0
95 K03724 0.573 1.21e-02 0.08237 0.001 100.0 0.000 93.8
116 K06925 0.578 6.76e-03 0.05551 0.066 100.0 0.046 100.0
51 K02027 0.580 1.21e-02 0.08237 0.038 100.0 0.029 100.0
91 K03601 0.586 7.13e-04 0.01595 0.025 100.0 0.017 100.0
162 K12982 0.587 7.19e-04 0.01595 0.001 50.0 0.000 37.5
40 K01693 0.592 8.21e-03 0.06368 0.031 100.0 0.027 100.0
45 K01848 0.594 8.38e-03 0.06417 0.001 75.0 0.000 68.8
157 K11211 0.597 2.21e-04 0.01144 0.001 58.3 0.000 25.0
52 K02028 0.598 5.19e-03 0.04620 0.055 100.0 0.045 100.0
18 K00878 0.605 7.67e-03 0.06068 0.026 100.0 0.019 100.0
93 K03656 0.619 5.19e-03 0.04620 0.001 91.7 0.000 62.5
12 K00375 0.638 1.52e-02 0.09613 0.015 100.0 0.011 100.0
101 K04096 0.644 1.29e-03 0.02001 0.038 100.0 0.027 100.0
137 K08310 0.645 1.05e-02 0.07429 0.003 66.7 0.001 68.8
133 K08151 0.648 1.31e-03 0.02017 0.001 66.7 0.001 37.5
163 K13243 0.649 1.73e-05 0.00473 0.002 50.0 0.000 43.8
21 K00943 0.650 9.50e-03 0.07046 0.032 100.0 0.023 100.0
1 K00020 0.660 9.38e-03 0.07004 0.003 100.0 0.001 81.2
97 K03923 0.660 9.29e-03 0.06975 0.002 75.0 0.001 68.8
123 K07234 0.662 2.33e-05 0.00555 0.001 66.7 0.000 37.5
183 K18893 0.662 3.56e-05 0.00668 0.001 58.3 0.000 31.2
108 K06042 0.664 1.14e-02 0.07929 0.010 100.0 0.007 100.0
127 K07478 0.672 3.41e-04 0.01358 0.097 100.0 0.067 100.0
67 K02341 0.676 2.98e-04 0.01336 0.052 100.0 0.032 100.0
81 K03216 0.679 1.56e-03 0.02216 0.032 100.0 0.024 100.0
132 K08094 0.680 8.05e-03 0.06291 0.002 58.3 0.000 50.0
118 K07040 0.681 9.50e-04 0.01750 0.028 100.0 0.019 100.0
54 K02030 0.682 2.29e-03 0.02731 0.055 100.0 0.043 100.0
69 K02434 0.685 3.12e-03 0.03254 0.025 100.0 0.020 100.0
70 K02435 0.691 6.76e-03 0.05551 0.020 100.0 0.016 100.0
113 K06446 0.694 1.98e-03 0.02551 0.001 100.0 0.001 93.8
169 K14155 0.697 2.33e-04 0.01173 0.041 100.0 0.027 100.0
187 K19416 0.707 9.34e-05 0.00882 0.001 58.3 0.000 12.5
147 K09780 0.708 1.80e-04 0.01049 0.001 58.3 0.000 12.5
148 K09801 0.715 5.80e-05 0.00722 0.001 58.3 0.000 31.2
176 K15539 0.722 1.35e-02 0.08859 0.003 83.3 0.001 81.2
41 K01749 0.726 5.59e-03 0.04852 0.012 100.0 0.008 100.0
151 K10536 0.728 7.69e-03 0.06072 0.014 100.0 0.010 100.0
96 K03785 0.739 2.25e-03 0.02719 0.021 100.0 0.012 100.0
62 K02193 0.743 1.32e-02 0.08658 0.004 100.0 0.002 100.0
112 K06206 0.748 1.28e-02 0.08509 0.009 100.0 0.005 100.0
73 K02492 0.749 1.53e-02 0.09685 0.010 100.0 0.005 100.0
164 K13292 0.753 2.14e-03 0.02619 0.019 100.0 0.012 100.0
100 K04083 0.753 4.60e-03 0.04232 0.019 100.0 0.012 100.0
171 K14260 0.764 6.70e-03 0.05539 0.010 100.0 0.006 100.0
39 K01626 0.765 5.62e-03 0.04855 0.027 100.0 0.019 100.0
138 K08316 0.767 7.18e-03 0.05770 0.011 100.0 0.006 100.0
26 K01090 0.771 4.47e-03 0.04148 0.010 100.0 0.006 100.0
68 K02433 0.772 9.93e-04 0.01783 0.024 100.0 0.017 100.0
92 K03625 0.772 1.13e-04 0.00952 0.056 100.0 0.039 100.0
78 K03060 0.772 5.86e-03 0.04999 0.021 100.0 0.013 100.0
76 K02654 0.772 6.11e-03 0.05169 0.015 100.0 0.009 100.0
175 K15531 0.773 1.62e-02 0.09978 0.009 100.0 0.005 100.0
126 K07461 0.778 1.02e-02 0.07323 0.026 100.0 0.018 93.8
65 K02334 0.783 1.41e-02 0.09116 0.015 100.0 0.008 100.0
63 K02203 0.785 8.88e-03 0.06728 0.008 100.0 0.005 100.0
120 K07098 0.788 9.43e-04 0.01750 0.044 100.0 0.025 100.0
33 K01494 0.791 1.13e-02 0.07898 0.009 100.0 0.004 100.0
160 K11928 0.796 2.90e-03 0.03083 0.018 100.0 0.013 100.0
85 K03413 0.812 5.24e-03 0.04631 0.020 100.0 0.010 100.0
14 K00641 0.813 8.67e-03 0.06619 0.028 100.0 0.019 100.0
37 K01524 0.813 9.79e-03 0.07170 0.020 100.0 0.015 100.0
53 K02029 0.814 5.38e-04 0.01529 0.061 100.0 0.041 100.0
159 K11606 0.816 5.23e-04 0.01529 0.002 83.3 0.000 68.8
55 K02035 0.829 8.28e-04 0.01659 0.021 100.0 0.012 100.0
64 K02283 0.831 1.62e-03 0.02255 0.024 100.0 0.014 100.0
83 K03273 0.831 1.48e-02 0.09446 0.012 100.0 0.005 100.0
130 K07738 0.832 2.18e-04 0.01144 0.033 100.0 0.020 100.0
177 K17677 0.833 2.22e-03 0.02691 0.008 100.0 0.004 100.0
32 K01436 0.838 1.63e-02 0.09995 0.002 75.0 0.000 81.2
6 K00241 0.847 1.02e-02 0.07323 0.040 100.0 0.025 100.0
80 K03179 0.855 1.48e-02 0.09430 0.015 100.0 0.008 100.0
84 K03306 0.865 3.94e-03 0.03800 0.004 100.0 0.002 100.0
44 K01845 0.866 7.08e-03 0.05714 0.013 100.0 0.011 100.0
124 K07263 0.867 9.33e-03 0.06995 0.013 100.0 0.005 100.0
79 K03074 0.884 1.45e-03 0.02150 0.002 75.0 0.000 50.0
104 K05589 0.898 1.79e-04 0.01049 0.002 50.0 0.000 25.0
158 K11605 0.904 7.19e-04 0.01595 0.002 91.7 0.000 62.5
2 K00104 0.908 1.10e-02 0.07753 0.011 100.0 0.008 100.0
182 K18476 0.910 6.27e-06 0.00356 0.001 75.0 0.001 25.0
150 K09974 0.916 3.57e-03 0.03565 0.011 100.0 0.005 100.0
86 K03500 0.921 4.67e-05 0.00704 0.018 100.0 0.010 100.0
5 K00209 0.923 6.87e-03 0.05595 0.002 91.7 0.000 56.2
50 K02012 0.925 7.63e-03 0.06056 0.005 66.7 0.000 68.8
167 K13788 0.927 6.28e-04 0.01586 0.002 91.7 0.000 68.8
72 K02471 0.930 9.83e-06 0.00356 0.002 91.7 0.000 56.2
24 K00989 0.936 8.77e-03 0.06672 0.013 100.0 0.006 100.0
58 K02062 0.941 3.19e-05 0.00668 0.002 83.3 0.000 43.8
59 K02073 0.950 2.35e-03 0.02737 0.017 100.0 0.008 100.0
25 K00997 0.956 1.62e-03 0.02255 0.014 100.0 0.008 100.0
184 K18926 0.962 9.22e-04 0.01750 0.000 66.7 0.000 68.8
77 K02777 0.963 1.15e-02 0.07953 0.004 100.0 0.003 93.8
35 K01512 0.964 2.28e-03 0.02731 0.013 100.0 0.007 100.0
94 K03684 0.965 8.20e-03 0.06368 0.010 100.0 0.004 100.0
165 K13497 0.966 1.54e-02 0.09697 0.008 100.0 0.009 100.0
29 K01207 0.975 5.20e-03 0.04622 0.019 100.0 0.008 100.0
15 K00690 0.989 1.18e-03 0.01928 0.011 100.0 0.006 100.0
74 K02549 0.999 1.38e-02 0.09023 0.007 100.0 0.003 100.0
129 K07726 1.003 3.70e-03 0.03654 0.011 100.0 0.005 100.0
34 K01496 1.004 1.25e-02 0.08437 0.013 100.0 0.016 100.0
178 K17686 1.004 1.89e-03 0.02475 0.008 100.0 0.004 100.0
47 K01922 1.009 1.58e-02 0.09884 0.005 83.3 0.002 87.5
109 K06077 1.010 1.61e-02 0.09954 0.008 91.7 0.002 93.8
82 K03272 1.011 1.59e-02 0.09910 0.008 100.0 0.003 100.0
46 K01894 1.018 1.26e-02 0.08446 0.006 100.0 0.002 93.8
57 K02050 1.020 1.44e-03 0.02147 0.020 100.0 0.016 100.0
154 K10806 1.041 1.63e-02 0.09995 0.005 83.3 0.001 81.2
3 K00164 1.103 1.45e-02 0.09300 0.005 91.7 0.002 93.8
111 K06195 1.106 1.04e-02 0.07393 0.007 91.7 0.002 93.8
28 K01198 1.107 1.53e-03 0.02193 0.015 100.0 0.007 100.0
172 K14445 1.119 1.55e-02 0.09751 0.011 91.7 0.004 100.0
114 K06864 1.131 4.28e-03 0.04010 0.008 100.0 0.003 100.0
43 K01792 1.136 6.57e-03 0.05465 0.011 100.0 0.003 100.0
98 K03980 1.149 2.84e-03 0.03042 0.008 100.0 0.002 100.0
31 K01304 1.152 6.57e-03 0.05465 0.002 58.3 0.000 62.5
149 K09928 1.162 8.84e-03 0.06708 0.005 75.0 0.001 68.8
143 K09131 1.188 4.84e-03 0.04391 0.008 91.7 0.003 93.8
181 K18095 1.210 1.36e-02 0.08859 0.006 83.3 0.002 93.8
8 K00254 1.211 5.63e-03 0.04857 0.008 100.0 0.002 100.0
17 K00801 1.224 7.23e-03 0.05805 0.004 83.3 0.001 87.5
13 K00380 1.242 1.19e-02 0.08164 0.009 100.0 0.006 100.0
152 K10679 1.244 7.02e-03 0.05680 0.008 100.0 0.003 93.8
142 K08680 1.266 3.15e-03 0.03279 0.008 100.0 0.002 100.0
56 K02049 1.271 2.21e-04 0.01144 0.017 100.0 0.006 100.0
168 K13821 1.278 5.92e-03 0.05040 0.006 83.3 0.002 100.0
49 K02007 1.319 2.73e-03 0.02977 0.010 91.7 0.005 93.8
180 K18094 1.326 3.71e-03 0.03659 0.006 83.3 0.002 87.5
110 K06181 1.338 2.50e-03 0.02806 0.008 100.0 0.002 100.0
60 K02077 1.354 8.90e-04 0.01736 0.007 100.0 0.002 100.0
146 K09769 1.364 6.94e-03 0.05636 0.008 100.0 0.003 93.8
89 K03578 1.367 2.95e-03 0.03119 0.008 100.0 0.004 100.0
136 K08282 1.388 3.63e-03 0.03602 0.006 83.3 0.002 93.8
125 K07318 1.450 1.98e-03 0.02551 0.005 91.7 0.001 62.5
103 K05541 1.455 1.05e-03 0.01817 0.009 100.0 0.002 100.0
90 K03579 1.480 7.27e-04 0.01600 0.004 83.3 0.001 87.5
38 K01598 1.587 8.78e-04 0.01728 0.006 75.0 0.001 62.5
121 K07102 1.610 3.27e-04 0.01358 0.007 83.3 0.001 93.8
23 K00968 1.620 1.15e-04 0.00954 0.004 75.0 0.001 56.2
22 K00955 1.667 9.66e-06 0.00356 0.004 75.0 0.000 50.0
179 K17733 1.846 3.59e-04 0.01358 0.007 66.7 0.001 50.012.5.11 T1 vs T2 (in women without T1D)
Function LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
2 K01668 0.680 3.95e-06 0.004329 0.001 81.8 0.000 50
6 K07234 0.786 1.83e-06 0.003338 0.001 90.9 0.001 55
4 K05952 0.860 1.76e-06 0.003338 0.001 63.6 0.000 30
1 K01166 0.883 3.13e-06 0.004291 0.001 81.8 0.000 45
3 K01674 0.892 3.81e-05 0.034838 0.001 90.9 0.001 45
5 K06212 0.941 6.01e-09 0.000033 0.001 90.9 0.000 4512.5.12 T2 vs T3 (in women without T1D)
[1] "No DA taxa found"12.5.13 T1 vs T3 (in women without T1D)
Function LogFC P.Val adj.P.Val T1:mean% T1Prev% T3:mean% T3Prev%
16 K02822 -1.537 3.19e-04 4.72e-02 0.002 81.8 0.006 100.0
19 K03293 -1.477 3.59e-04 4.92e-02 0.007 100.0 0.014 100.0
17 K02851 -1.381 3.42e-04 4.81e-02 0.005 90.9 0.008 100.0
11 K01807 -1.311 9.93e-04 9.89e-02 0.007 100.0 0.013 100.0
46 K16925 -1.301 4.34e-04 5.80e-02 0.002 72.7 0.005 88.2
1 K00171 -1.277 4.94e-06 2.46e-03 0.001 81.8 0.005 94.1
6 K01354 -1.261 2.24e-04 3.83e-02 0.001 81.8 0.004 88.2
32 K07467 -1.240 2.45e-05 6.40e-03 0.001 90.9 0.005 94.1
24 K05794 -1.216 6.98e-04 8.14e-02 0.002 81.8 0.005 88.2
21 K03762 -1.189 2.45e-04 4.06e-02 0.001 100.0 0.004 100.0
15 K02588 -1.092 8.62e-04 9.26e-02 0.001 100.0 0.005 94.1
4 K00997 -1.085 5.69e-04 7.26e-02 0.014 100.0 0.023 100.0
8 K01626 -0.957 9.37e-04 9.77e-02 0.018 100.0 0.031 100.0
31 K07454 -0.932 1.22e-05 4.08e-03 0.000 36.4 0.001 70.6
51 K19509 -0.861 5.57e-05 1.22e-02 0.000 45.5 0.001 64.7
33 K07654 -0.852 9.91e-04 9.89e-02 0.000 54.5 0.002 82.4
28 K06605 -0.829 6.05e-04 7.53e-02 0.000 63.6 0.002 76.5
7 K01560 -0.750 3.80e-05 9.05e-03 0.000 27.3 0.001 64.7
48 K18893 0.534 9.45e-04 9.77e-02 0.000 81.8 0.000 35.3
49 K18991 0.542 1.49e-04 2.81e-02 0.000 81.8 0.000 41.2
3 K00979 0.545 8.10e-04 8.88e-02 0.055 100.0 0.041 100.0
47 K18785 0.619 1.84e-04 3.25e-02 0.090 100.0 0.065 100.0
12 K02339 0.629 2.52e-04 4.06e-02 0.000 72.7 0.000 29.4
50 K19431 0.633 2.64e-05 6.59e-03 0.000 81.8 0.000 23.5
44 K15461 0.635 1.81e-05 4.96e-03 0.000 90.9 0.000 52.9
29 K07084 0.658 1.01e-05 3.69e-03 0.000 81.8 0.000 35.3
37 K10094 0.661 1.02e-04 1.99e-02 0.000 72.7 0.000 23.5
18 K03116 0.671 1.68e-04 3.07e-02 0.105 100.0 0.070 100.0
34 K08990 0.676 7.52e-06 3.17e-03 0.000 81.8 0.000 29.4
23 K05685 0.730 5.28e-07 3.62e-04 0.000 90.9 0.000 29.4
2 K00368 0.757 6.68e-06 3.05e-03 0.001 72.7 0.000 29.4
26 K06194 0.758 7.83e-05 1.65e-02 0.001 81.8 0.000 70.6
20 K03656 0.782 6.84e-04 8.14e-02 0.001 90.9 0.000 64.7
42 K12984 0.790 8.55e-05 1.74e-02 0.001 81.8 0.000 41.2
38 K11211 0.803 2.98e-06 1.63e-03 0.001 90.9 0.000 29.4
43 K13634 0.804 1.37e-06 8.36e-04 0.000 72.7 0.000 17.6
41 K12982 0.804 1.27e-05 4.08e-03 0.001 81.8 0.000 23.5
45 K15984 0.848 3.00e-04 4.57e-02 0.001 90.9 0.000 29.4
9 K01668 0.849 3.04e-08 4.17e-05 0.001 81.8 0.000 23.5
40 K12145 0.884 2.95e-04 4.57e-02 0.001 81.8 0.000 29.4
22 K05589 0.894 3.33e-04 4.80e-02 0.001 81.8 0.000 29.4
13 K02344 0.915 1.42e-05 4.33e-03 0.001 81.8 0.000 29.4
39 K11607 0.934 1.85e-07 1.69e-04 0.001 81.8 0.000 29.4
14 K02471 0.946 1.80e-05 4.96e-03 0.001 90.9 0.000 58.8
10 K01674 0.975 9.04e-06 3.54e-03 0.001 90.9 0.000 29.4
5 K01166 0.999 2.17e-07 1.70e-04 0.001 81.8 0.000 29.4
35 K09801 0.999 1.58e-07 1.69e-04 0.001 81.8 0.000 23.5
36 K09824 1.017 4.02e-05 9.17e-03 0.001 81.8 0.000 52.9
25 K05952 1.022 2.84e-08 4.17e-05 0.001 63.6 0.000 11.8
27 K06212 1.029 4.13e-10 2.26e-06 0.001 90.9 0.000 35.3
30 K07234 1.031 1.93e-09 5.27e-06 0.001 90.9 0.000 35.3[1] 2013 Functional analysis (MetaCyc reactions)
13.1 Bar plots taxonomy
13.2 Functional Alpha diversity (Days)
13.3 Functional Alpha diversity (Trimesters)
Call:
geeglm(formula = Observed ~ t1dfactor * Tri + age_c + nullip +
bmi_c + HLA + SeqRun, data = DivCal_R_df, id = motherid,
corstr = "exchangeable")
Coefficients:
Estimate Std.err Wald Pr(>|W|)
(Intercept) 1883.99 66.29 807.78 <2e-16 ***
t1dfactorT1D 138.79 86.88 2.55 0.110
TriT2 71.54 52.33 1.87 0.172
TriT3 94.49 62.93 2.25 0.133
age_c 3.76 5.27 0.51 0.476
nullipYes -97.91 39.52 6.14 0.013 *
bmi_c 1.47 4.55 0.10 0.747
HLADRXX 28.64 53.34 0.29 0.591
HLAGroup3o4 44.08 49.75 0.78 0.376
SeqRun3 38.76 48.95 0.63 0.428
SeqRun4 82.61 50.33 2.69 0.101
SeqRun6 -11.79 58.00 0.04 0.839
t1dfactorT1D:TriT2 -94.46 97.11 0.95 0.331
t1dfactorT1D:TriT3 -116.83 101.27 1.33 0.249
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Estimated Scale Parameters:
Estimate Std.err
(Intercept) 29167 5010
Correlation: Structure = exchangeable Link = identity
Estimated Correlation Parameters:
Estimate Std.err
alpha 0.115 0.178
Number of clusters: 83 Maximum cluster size: 3 13.4 Beta diversity analysis
13.4.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.096 0.0318 1.85 0.051 0.001 ***
Days 1 0.018 0.0181 1.05 0.010 0.110
T1D_Time_Interaction 1 0.094 0.0939 5.45 0.050 0.049 *
Age 1 0.058 0.0583 3.38 0.031 0.991
Parity 1 0.038 0.0380 2.20 0.020 0.184
BMI 1 0.029 0.0290 1.68 0.015 0.971
HLA 2 0.074 0.0370 2.15 0.039 0.593
T1Dstatus 1 0.022 0.0224 1.30 0.012 0.901
Residuals 84 1.448 0.0172 0.771 0.612
Total 95 1.877 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.04913.4.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.040 0.0134 0.583 0.084 0.96
Nulliparous 1 0.023 0.0227 0.984 0.048 0.47
Age_LMP 1 0.023 0.0227 0.985 0.048 0.45
BMI_conception 1 0.016 0.0156 0.677 0.033 0.75
HLA.6DRML 2 0.040 0.0202 0.875 0.084 0.64
T1Dstatus 1 0.036 0.0363 1.572 0.076 0.11
Residuals 13 0.300 0.0231 0.628
Total 22 0.478 1.000 [1] 0.113Beta diversity Plot
13.4.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.067 0.0223 1.184 0.112 0.24
Nulliparous 1 0.021 0.0212 1.125 0.035 0.33
Age_LMP 1 0.026 0.0261 1.383 0.044 0.18
BMI_conception 1 0.010 0.0103 0.548 0.017 0.87
HLA.6DRML 2 0.035 0.0175 0.927 0.058 0.54
T1Dstatus 1 0.023 0.0233 1.240 0.039 0.25
Residuals 22 0.414 0.0188 0.694
Total 31 0.597 1.000 [1] 0.247Beta diversity Plot
13.4.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.041 0.0136 0.643 0.062 0.934
Nulliparous 1 0.016 0.0162 0.769 0.025 0.660
Age_LMP 1 0.022 0.0222 1.052 0.034 0.390
BMI_conception 1 0.022 0.0220 1.039 0.033 0.407
HLA.6DRML 2 0.032 0.0162 0.768 0.049 0.756
T1Dstatus 1 0.063 0.0626 2.964 0.095 0.004 **
Residuals 22 0.465 0.0211 0.703
Total 31 0.661 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.004Beta diversity Plot
13.4.5 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.060 0.0301 1.97 0.067 0.72
seqRun 3 0.096 0.0320 2.09 0.107 0.73
Age 1 0.025 0.0252 1.65 0.028 0.93
Parity 1 0.081 0.0806 5.28 0.090 0.10
BMI 1 0.048 0.0479 3.14 0.053 0.40
Tri 2 0.023 0.0113 0.74 0.025 0.40
Residuals 37 0.565 0.0153 0.630 0.80
Total 47 0.897 1.000 Beta diversity Plot
13.4.6 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.085 0.0425 3.03 0.097 0.390
seqRun 3 0.091 0.0305 2.17 0.104 0.848
Age 1 0.101 0.1009 7.19 0.115 0.099 .
Parity 1 0.024 0.0242 1.73 0.027 0.955
BMI 1 0.040 0.0396 2.82 0.045 0.042 *
Tri 2 0.020 0.0101 0.72 0.023 0.492
Residuals 37 0.519 0.0140 0.590 0.324
Total 47 0.880 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
13.5 Differential abundance analysis
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3
Down 0 17 0 0 0 0 1 0 0
NotSig 3014 2996 3014 3003 3014 3014 3009 3014 3014
Up 0 1 0 11 0 0 4 0 0
T1DT1vsT3 noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 1 0 0 1
NotSig 2997 3014 3014 3009
Up 16 0 0 4Results for contrasts with significant differentially abundant strains shown below
13.5.1 Across all trimesters (T1D vs non-T1D)
[1] "No DA taxa found"13.5.2 Only Trimester 1 (nonT1D vs T1D)
Function LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
2 DHBAMPLIG-RXN -2.051 1.04e-04 0.0224 0.001 100.0 0.004 100.0
6 RXN-14814 -2.051 1.04e-04 0.0224 0.001 100.0 0.004 100.0
1 3.4.21.87-RXN -1.426 1.77e-05 0.0213 0.000 50.0 0.000 37.5
7 RXN0-305 -1.420 8.08e-05 0.0213 0.000 56.2 0.001 75.0
5 RXN-12444 -1.190 7.48e-04 0.0835 0.000 68.8 0.001 56.2
3 R15-RXN -1.140 4.68e-04 0.0613 0.000 68.8 0.001 68.8
4 RXN-12353 -0.966 1.84e-04 0.0309 0.000 37.5 0.000 62.5
8 RXN0-984 -0.966 1.84e-04 0.0309 0.000 37.5 0.000 62.5
9 RXN0-985 -0.966 1.84e-04 0.0309 0.000 37.5 0.000 62.5
10 RXN0-986 -0.966 1.84e-04 0.0309 0.000 37.5 0.000 62.513.5.3 Only Trimester 2 (nonT1D vs T1D)
[1] "No DA taxa found"13.5.4 Only Trimester 3 (nonT1D vs T1D)
Function LogFC P.Val adj.P.Val nonT1D:mean% Prev%
27 RXN-14469 -1.149 2.95e-04 0.05930 0.000 43.8
11 CYSTATHIONINE-BETA-SYNTHASE-RXN 0.938 4.78e-04 0.08094 0.001 56.2
6 ADENINE-DEAMINASE-RXN 0.958 1.03e-03 0.09978 0.045 100.0
21 RXN-11860 1.009 5.16e-04 0.08094 0.059 100.0
22 RXN-11865 1.009 5.16e-04 0.08094 0.059 100.0
14 GLUC1PADENYLTRANS-RXN 1.032 9.10e-04 0.09794 0.147 100.0
15 GLUTAMATESYN-RXN 1.093 9.60e-04 0.09972 0.085 100.0
30 THIAZOLSYN3-RXN 1.132 6.56e-04 0.08094 0.048 100.0
26 RXN-14148 1.140 4.28e-05 0.01844 0.002 56.2
13 GALACTURIDYLYLTRANS-RXN 1.159 5.16e-04 0.08094 0.049 100.0
7 BRANCHED-CHAINAMINOTRANSFERILEU-RXN 1.168 7.67e-05 0.02312 0.060 100.0
8 BRANCHED-CHAINAMINOTRANSFERLEU-RXN 1.168 7.67e-05 0.02312 0.060 100.0
9 BRANCHED-CHAINAMINOTRANSFERVAL-RXN 1.168 7.67e-05 0.02312 0.060 100.0
4 6.3.5.7-RXN 1.191 6.98e-04 0.08094 0.065 100.0
2 3.4.21.88-RXN 1.200 5.54e-04 0.08094 0.057 100.0
20 RXN-11322 1.222 2.67e-04 0.05746 0.076 100.0
28 RXN-2043 1.239 6.85e-04 0.08094 0.033 100.0
3 5-DEHYDRO-2-DEOXYGLUCONOKINASE-RXN 1.259 1.32e-04 0.03621 0.001 68.8
17 PHOSPHAGLYPSYN-RXN 1.293 2.40e-04 0.05746 0.063 100.0
29 RXN-8850 1.369 9.98e-04 0.09978 0.034 100.0
5 ACYLPHOSPHATASE-RXN 1.404 2.59e-04 0.05746 0.015 100.0
12 DIHYDROPYRIMIDINASE-RXN 1.518 6.45e-04 0.08094 0.003 93.8
18 RXN-11211 1.518 6.45e-04 0.08094 0.003 93.8
19 RXN-11217 1.518 6.45e-04 0.08094 0.003 93.8
16 MYO-INOSOSE-2-DEHYDRATASE-RXN 1.661 8.06e-04 0.08994 0.005 100.0
10 CYCLOMALTODEXTRINASE-RXN 1.827 4.25e-06 0.00320 0.003 68.8
1 1.1.1.188-RXN 1.878 3.82e-05 0.01844 0.004 62.5
23 RXN-12558 1.956 2.03e-06 0.00204 0.005 87.5
24 RXN-12559 1.956 2.03e-06 0.00204 0.005 87.5
31 TRANS-2-ENOYL-COA-REDUCTASE-NAD+-RXN 1.956 2.03e-06 0.00204 0.005 87.5
25 RXN-13028 2.348 4.01e-05 0.01844 0.007 87.5
T1D:mean% T1D:Prev%
27 0.001 68.8
11 0.000 18.8
6 0.031 100.0
21 0.033 100.0
22 0.033 100.0
14 0.087 100.0
15 0.053 100.0
30 0.025 100.0
26 0.000 25.0
13 0.029 100.0
7 0.032 100.0
8 0.032 100.0
9 0.032 100.0
4 0.032 100.0
2 0.032 100.0
20 0.037 100.0
28 0.017 100.0
3 0.000 43.8
17 0.033 100.0
29 0.017 100.0
5 0.008 100.0
12 0.001 87.5
18 0.001 87.5
19 0.001 87.5
16 0.002 87.5
10 0.000 43.8
1 0.000 43.8
23 0.000 56.2
24 0.000 56.2
31 0.000 56.2
25 0.000 81.213.5.5 T1 vs T2 (All data)
[1] "No DA taxa found"13.5.6 T2 vs T3 (All data)
[1] "No DA taxa"13.5.7 T1 vs T3 (All data)
Function LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean%
1 2-OXOPENT-4-ENOATE-HYDRATASE-RXN -0.537 1.64e-04 8.22e-02 0.000 47.8 0.001
2 3.1.21.1-RXN -0.934 8.72e-06 5.25e-03 0.001 47.8 0.001
3 3.4.24.57-RXN 0.701 5.75e-06 4.33e-03 0.001 69.6 0.000
4 6PGLUCONDEHYDROG-RXN 0.784 1.32e-06 1.33e-03 0.001 82.6 0.000
5 RXN-11328 0.711 8.34e-09 1.26e-05 0.001 73.9 0.000
6 RXN-16750 0.711 8.34e-09 1.26e-05 0.001 73.9 0.000
T2Prev% T3:mean% T3Prev%
1 42.5 0.001 63.6
2 57.5 0.001 75.8
3 50.0 0.000 33.3
4 75.0 0.000 39.4
5 50.0 0.000 27.3
6 50.0 0.000 27.313.5.8 T1 vs T2 (in women with T1D)
[1] "No DA taxa found"13.5.9 T2 vs T3 (in women with T1D)
[1] "No DA taxa found"13.5.10 T1 vs T3 (in women with T1D)
Function LogFC P.Val adj.P.Val T1:mean% T1Prev%
7 3.1.21.1-RXN -1.064 2.53e-04 0.0448 0.001 50.0
31 N-ACETYLNEURAMINATE-SYNTHASE-RXN -0.965 2.57e-03 0.0712 0.001 66.7
58 RXN0-5228 -0.727 4.84e-03 0.0844 0.009 100.0
38 RXN-11596 -0.700 1.03e-02 0.0948 0.009 100.0
30 MHPCHYDROL-RXN -0.684 1.20e-03 0.0544 0.000 33.3
41 RXN-12070 -0.684 1.20e-03 0.0544 0.000 33.3
3 2-OXOPENT-4-ENOATE-HYDRATASE-RXN -0.662 8.68e-04 0.0544 0.001 41.7
49 RXN-15299 -0.647 4.07e-04 0.0544 0.000 16.7
18 GKI-RXN -0.543 8.14e-04 0.0544 0.000 33.3
4 2.1.1.72-RXN 0.508 4.02e-03 0.0787 0.235 100.0
54 RXN-8668 0.527 1.91e-03 0.0695 0.054 100.0
37 RXN-11328 0.533 8.35e-04 0.0544 0.001 58.3
51 RXN-16750 0.533 8.35e-04 0.0544 0.001 58.3
24 H2PTEROATESYNTH-RXN 0.549 1.21e-03 0.0544 0.038 100.0
55 RXN0-305 0.551 8.88e-03 0.0948 0.003 75.0
26 HOMOSERKIN-RXN 0.552 3.04e-03 0.0718 0.040 100.0
5 2.7.9.3-RXN 0.553 8.36e-03 0.0948 0.022 100.0
13 AMIDASE-RXN 0.559 7.36e-06 0.0037 0.001 66.7
22 GUANIDINOBUTANAMIDE-NH3-RXN 0.559 7.36e-06 0.0037 0.001 66.7
34 R311-RXN 0.559 7.36e-06 0.0037 0.001 66.7
47 RXN-14727 0.559 7.36e-06 0.0037 0.001 66.7
48 RXN-14728 0.559 7.36e-06 0.0037 0.001 66.7
66 RXNN-404 0.559 7.36e-06 0.0037 0.001 66.7
39 RXN-11860 0.562 3.07e-03 0.0718 0.044 100.0
40 RXN-11865 0.562 3.07e-03 0.0718 0.044 100.0
23 H2NEOPTERINP3PYROPHOSPHOHYDRO-RXN 0.598 6.35e-03 0.0894 0.002 66.7
19 GLUC1PURIDYLTRANS-RXN 0.613 7.75e-03 0.0948 0.027 100.0
44 RXN-14047 0.625 9.78e-03 0.0948 0.013 100.0
16 DTMPKI-RXN 0.646 2.32e-03 0.0712 0.041 100.0
29 MANNPISOM-RXN 0.650 1.98e-03 0.0701 0.051 100.0
67 THIAZOLSYN3-RXN 0.655 2.57e-03 0.0712 0.037 100.0
17 ENTDB-RXN 0.671 1.05e-02 0.0956 0.027 100.0
50 RXN-15889 0.671 1.05e-02 0.0956 0.027 100.0
33 PORPHOBILSYNTH-RXN 0.696 5.78e-03 0.0872 0.022 100.0
12 ACYLPHOSPHATASE-RXN 0.705 4.71e-03 0.0843 0.012 100.0
25 HOLO-ACP-SYNTH-RXN 0.718 5.77e-03 0.0872 0.027 100.0
35 RXN-10994 0.718 5.77e-03 0.0872 0.027 100.0
52 RXN-16759 0.718 5.77e-03 0.0872 0.027 100.0
21 GSAAMINOTRANS-RXN 0.723 6.35e-03 0.0894 0.021 100.0
46 RXN-14569 0.729 1.81e-03 0.0684 0.026 100.0
9 3.1.26.12-RXN 0.763 1.35e-03 0.0544 0.001 50.0
59 RXN0-6478 0.763 1.35e-03 0.0544 0.001 50.0
60 RXN0-6485 0.763 1.35e-03 0.0544 0.001 50.0
62 RXN0-6521 0.763 1.35e-03 0.0544 0.001 50.0
63 RXN0-6522 0.763 1.35e-03 0.0544 0.001 50.0
64 RXN0-6523 0.763 1.35e-03 0.0544 0.001 50.0
15 DIHYDROOROTATE-DEHYDROGENASE-RXN 0.764 8.78e-03 0.0948 0.025 100.0
61 RXN0-6491 0.764 8.78e-03 0.0948 0.025 100.0
65 RXN0-6554 0.764 8.78e-03 0.0948 0.025 100.0
32 OHMETHYLBILANESYN-RXN 0.787 3.81e-04 0.0544 0.019 100.0
53 RXN-7644 0.803 7.91e-04 0.0544 0.013 100.0
11 6.1.1.23-RXN 0.808 3.26e-04 0.0544 0.001 66.7
2 1.3.1.2-RXN 0.808 9.40e-03 0.0948 0.001 75.0
36 RXN-11209 0.808 9.40e-03 0.0948 0.001 75.0
27 L-IDITOL-2-DEHYDROGENASE-RXN 0.816 5.55e-04 0.0544 0.013 100.0
10 3.4.21.87-RXN 0.822 3.07e-05 0.0103 0.001 58.3
56 RXN0-3281 0.837 2.22e-04 0.0440 0.002 66.7
57 RXN0-4301 0.855 4.32e-03 0.0811 0.013 100.0
14 DCTP-DEAM-RXN 0.857 5.68e-03 0.0872 0.009 100.0
45 RXN-14118 0.857 5.68e-03 0.0872 0.009 100.0
42 RXN-12558 0.864 1.11e-03 0.0544 0.001 83.3
43 RXN-12559 0.864 1.11e-03 0.0544 0.001 83.3
68 TRANS-2-ENOYL-COA-REDUCTASE-NAD+-RXN 0.864 1.11e-03 0.0544 0.001 83.3
28 LYSDECARBOX-RXN 0.921 5.18e-03 0.0856 0.002 91.7
1 1.2.1.2-RXN 0.980 9.42e-03 0.0948 0.005 91.7
20 GLUTRNAREDUCT-RXN 1.013 6.05e-04 0.0544 0.014 100.0
8 3.1.21.5-RXN 1.085 1.53e-03 0.0598 0.002 100.0
6 2OXOGLUTDECARB-RXN 1.166 9.10e-03 0.0948 0.004 91.7
T3:mean% T3Prev%
7 0.002 87.5
31 0.002 68.8
58 0.014 100.0
38 0.014 100.0
30 0.001 75.0
41 0.001 75.0
3 0.001 56.2
49 0.001 50.0
18 0.001 50.0
4 0.188 100.0
54 0.041 100.0
37 0.000 25.0
51 0.000 25.0
24 0.025 100.0
55 0.001 75.0
26 0.028 100.0
5 0.016 100.0
13 0.000 43.8
22 0.000 43.8
34 0.000 43.8
47 0.000 43.8
48 0.000 43.8
66 0.000 43.8
39 0.033 100.0
40 0.033 100.0
23 0.001 56.2
19 0.018 100.0
44 0.010 100.0
16 0.031 100.0
29 0.036 100.0
67 0.025 100.0
17 0.017 100.0
50 0.017 100.0
33 0.015 100.0
12 0.008 100.0
25 0.017 100.0
35 0.017 100.0
52 0.017 100.0
21 0.016 100.0
46 0.017 100.0
9 0.000 31.2
59 0.000 31.2
60 0.000 31.2
62 0.000 31.2
63 0.000 31.2
64 0.000 31.2
15 0.018 100.0
61 0.018 100.0
65 0.018 100.0
32 0.011 100.0
53 0.008 100.0
11 0.000 31.2
2 0.000 75.0
36 0.000 75.0
27 0.008 100.0
10 0.000 37.5
56 0.001 50.0
57 0.007 100.0
14 0.004 100.0
45 0.004 100.0
42 0.000 56.2
43 0.000 56.2
68 0.000 56.2
28 0.001 93.8
1 0.001 87.5
20 0.007 100.0
8 0.002 68.8
6 0.001 100.013.5.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa found"13.5.12 T2 vs T3 (in women without T1D)
Function LogFC P.Val adj.P.Val mean% Prev%
T2 RXN-14148 -0.663 2.69e-05 0.0811 0.000 30.0
T3 RXN-14148 -0.663 2.69e-05 0.0811 0.002 58.813.5.13 T1 vs T3 (in women without T1D)
Function LogFC P.Val adj.P.Val T1:mean% T1Prev% T3:mean% T3Prev%
6 NAG1P-URIDYLTRANS-RXN -1.317 2.20e-04 0.076366 0.002 100.0 0.006 100.0
5 MMUM-RXN -1.152 3.16e-04 0.095382 0.000 90.9 0.003 88.2
4 HISTCYCLOHYD-RXN -1.101 1.01e-04 0.050762 0.021 100.0 0.042 100.0
1 3.4.21.83-RXN -1.095 5.99e-05 0.036124 0.000 72.7 0.002 76.5
7 RXN-11328 0.889 3.17e-07 0.000478 0.000 90.9 0.000 29.4
8 RXN-16750 0.889 3.17e-07 0.000478 0.000 90.9 0.000 29.4
2 3.4.24.57-RXN 1.037 4.58e-06 0.003449 0.001 90.9 0.000 41.2
3 6PGLUCONDEHYDROG-RXN 1.127 1.31e-06 0.001320 0.001 90.9 0.000 41.2[1] 28